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Lead Data Scientist

We are looking for a Lead Data Scientist to own complex quantitative and risk modeling projects from problem definition through implementation. This is a highly visible role where your models will directly influence multi-million-dollar business opportunities and be presented to executive stakeholders.

What You’ll Do

• Build, evaluate, and validate quantitative and risk models.
• Work with large financial and credit datasets.
• Develop models using Python, SQL, and gradient boosting techniques.
• Translate model outputs into measurable financial and dollar impact.
• Own projects end-to-end, from defining the problem through implementation.
• Present technical findings and recommendations to senior and executive stakeholders.
• Defend models and methodology during external audits.
• Help identify and quantify significant financial opportunities.
• Provide technical guidance and support to other team members.

What We’re Looking For

• 8+ years of data science/modeling experience
• Strong Python and SQL skills.
• Strong data modeling experience.
• Strong mathematical and statistical foundation.
• Experience with gradient boosting models.
• Proven ability to independently lead projects end-to-end.
• Excellent communication and presentation skills.
• Comfortable explaining technical work and model results to executives.
• Experience working through external audits and defending models.
• Finance/risk modeling experience within a regulated industry is required.

Required Domain Experience

You should have experience in areas such as:

• Credit risk modeling
• Financial or loss modeling
• Probability of Default (PD) modeling
• Credit scorecards
• Payment behavior modeling
• Credit attribute modeling
• Mortgage, credit card, banking, or credit bureau data
• Risk modeling within a regulated financial institution

Education

• Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, Quantitative Engineering, or another highly quantitative field.
• Master’s degree in Data Science or a related quantitative discipline preferred.

The Ideal Candidate

This role is suited to a senior-level Data Scientist who can operate independently, drive complex projects, and communicate confidently with both technical and executive audiences.

Location: Tempe, AZ preferred; Dallas or Atlanta also considered
Working Model: Hybrid, 4 days per week (Monday-Thursday)
Compensation: $140,000-$150,000 base
Visa: U.S. Citizen or Green Card holder only

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LEAD DATA SCIENTIST – CREDIT RISK & ADVANCED ANALYTICS

TEMPE, AZ (HYBRID)

$140,000 – $150,000 BASE + ANNUAL BONUS

The Opportunity Join a high-impact Analytics team focused on solving complex business challenges through advanced data science, predictive modeling, and risk analytics.

This is a highly visible leadership role where you’ll partner directly with executives and cross-functional stakeholders to influence key business decisions, improve customer outcomes, and drive measurable financial impact.

You’ll own projects from concept through implementation, applying machine learning, statistical modeling, and business insight to deliver solutions that make a real difference.

What You’ll Do

• Lead analytical initiatives from problem definition through implementation and measurement
• Develop predictive models to support business strategy, financial forecasting, and risk assessment initiatives
• Leverage machine learning techniques such as gradient boosting, random forests, clustering, and segmentation to generate actionable insights
• Identify trends, quantify opportunities, and uncover root causes within large and complex datasets
• Collaborate with senior stakeholders to translate business challenges into analytical solutions
• Present findings and recommendations to leadership through compelling data storytelling and executive presentations
• Guide and mentor less experienced team members on project execution and analytical methodologies
• Build scalable processes and analytical frameworks that improve business performance over time

What We’re Looking For

• 8+ years of experience in data science, quantitative analytics, predictive modeling, or risk analytics
• Experience applying statistical and machine learning techniques to real-world business problems
• Advanced Python and SQL skills with experience working across large, complex datasets
• Strong understanding of predictive modeling, segmentation, experimentation, and statistical analysis
• Proven track record of influencing business decisions through data-driven recommendations
• Excellent communication skills with the ability to explain complex concepts to executive audiences
• Experience leading initiatives independently with minimal direction
• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Economics, Engineering, or a related discipline

Nice to Have

• Master’s degree in a quantitative discipline
• Experience within financial services, consumer lending, real estate, healthcare, or other regulated industries
• Background in risk management, portfolio analytics, or credit-related modeling
• Exposure to model validation, governance, audit, or regulatory review processes
• Knowledge of cloud-based data environments including AWS and Snowflake
• Experience utilizing bureau data, scorecards, or advanced forecasting methodologies

Why This Role

• High-visibility role with regular interaction with executive leadership
• Opportunity to drive business outcomes through production-ready analytics and machine learning
• Strong autonomy and ownership over projects and strategy
• Work on initiatives with measurable multi-million-dollar business impact
• Mentor and influence without direct people-management responsibilities
• Collaborative, supportive culture that values innovation, curiosity, and continuous improvement
• Opportunity to see your models implemented and your work recognized across the organization

If you’re a data science leader who enjoys solving complex business problems, influencing executive decisions, and building predictive models that drive real-world results, we’d love to connect.

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Lead Data Scientist

Location: Hybrid (Tempe, AZ preferred; Dallas, TX or Atlanta, GA also considered)

Schedule: 4 days onsite per week (Monday-Thursday)

Compensation: $130-145,000 base salary + bonus eligibility

Overview

A leading organization is seeking a Lead Data Scientist to drive advanced risk and financial modeling initiatives that directly influence business performance. This is a highly visible individual contributor role for a senior-level data scientist who can independently lead complex projects, quantify business impact, and effectively communicate insights to executive stakeholders.

This team is responsible for identifying significant financial opportunities, developing predictive models, and delivering measurable outcomes. Success in this role requires strong technical expertise, business acumen, and the ability to defend models in regulated environments.

Responsibilities

• Lead end-to-end data science projects from problem definition through implementation.
• Develop, validate, and monitor predictive and risk models using large-scale financial and customer datasets.
• Apply advanced statistical and machine learning techniques, including gradient boosting models.
• Translate model outputs into actionable business recommendations and financial impact.
• Present findings, model performance, and recommendations to senior leadership and executive stakeholders.
• Support model governance activities, audits, and validation reviews.
• Mentor and support team members while serving as a technical leader within the organization.

Required Qualifications

• 8+ years of experience in data science, quantitative analytics, or predictive modeling.
• Strong background in finance, credit, or risk modeling within a regulated industry.
• Advanced Python and SQL skills.
• Strong foundation in mathematics, statistics, and predictive modeling.
• Experience building and validating models used for financial or risk-related decision making.
• Experience presenting technical concepts and model results to executive audiences.
• Proven ability to independently own and deliver complex projects.
• Experience supporting external audits and defending analytical models.

Preferred Experience

Experience in one or more of the following areas:

• Credit risk modeling
• Probability of Default (PD) modeling
• Credit loss or loss forecasting models
• Scorecard development
• Payment behavior analytics
• Banking, lending, mortgage, credit card, or credit bureau data
• Financial impact and portfolio analysis

Education

• Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or another quantitative discipline required.
• Master’s degree in Data Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field preferred.

Why Join?

• Direct ownership of high-value analytics initiatives.
• Opportunity to see models implemented and tied to measurable business outcomes.
• Significant executive exposure and influence.
• High-impact, collaborative team where individual contributions are highly visible.
• Ability to drive projects that identify and deliver multi-million-dollar business opportunities.

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Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

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Applied AI Engineer, Product and Delivery | Hybrid Portland, ME or Remote (East Coast / Chicago) | $225,000 to $275,000 plus equity

Most AI job ads ask for an engineer who can tolerate the business. This one is the reverse.

We are hiring someone whose core strength is problem solving and commercial judgement, and who has started building with AI rather than just talking about it. If you are the person on your team who takes a vague question from an operator, works out what actually needs answering, and has recently been prototyping your own tooling with LLMs, read on.

The Company

A newly independent company, spun out of the value creation team of a private equity firm. Its proprietary platform builds a digital twin of an organisation, simulating its people, processes and systems to produce an actionable roadmap for AI-driven value creation. The founding team comes from quantitative finance, top-tier strategy consulting and leading analytics and technology firms. The work is evidence-based, auditable and used by investors and management teams to make real decisions about real businesses.

This is a founding-stage team. You will shape what gets built.

The Role

You sit between the consultants and analysts doing client work and the engineers building the product. Your job is to close the gap between them.

• Sit with consultants and data analysts, watch the work, and find where it is slow, manual or error-prone
• Take an ambiguous business problem and sharpen it into a requirement someone can build against
• Design and build LLM-powered prototypes to test whether an idea is worth pursuing
• Define what a good output looks like and build the checks that prove it
• Partner with software engineers to productionise what works, and drive adoption into the delivery workflow
• Lead design reviews and mentor the analysts and engineers building alongside you
• Track new models, frameworks and agentic tooling, and form a view on what is worth adopting

What We Are Looking For

The non-negotiables:

• Problem solving. You scope ruthlessly. You know the difference between the analysis that is complete and the analysis that is sufficient, and you ship the second one
• Business acumen. You understand how an operational change shows up in the numbers. P&L, EBITDA, labour cost. You can connect a technical output to a client’s investment thesis
• Operator exposure. You have worked directly with the people running a business, not adjacent to them. Your work changed what someone did on Monday
• Quality instinct. You check your own work by reflex. You can tell us about a time you caught something before it went out, and what you changed afterwards
• Strong SQL and the ability to build, not just specify

Big plus:

• Applied AI experience, at any depth. Internal tools, automated workflows, agent prototypes, LLM-assisted analysis. What matters is that you have built something real and learned where it falls over
• Python
• Fluency with agentic development tooling such as Claude Code, subagents and custom skills
• LangChain, LangGraph or similar orchestration frameworks
• Experience with LLM-as-judge evaluation patterns
• Consulting, private equity or another deadline-driven client-service background
• Forward-deployed or solutions work where you built something for one customer and then generalised it into product

You do not need a background as a machine learning engineer. Data analysts, analytics leads, business operations people, consultants and value creation professionals who have started building with AI are exactly who we want to hear from.

What Is On Offer

• Cash compensation of $225,000 to $275,000
• Equity in a newly independent business at the point of spin-out
• Hybrid in Portland, ME preferred, with fully remote considered for candidates on the East Coast or in Chicago
• Direct influence over the product and the technical direction, on a team small enough that your judgement carries

How to Apply

Apply through this advert or get in touch for a confidential conversation.

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Senior Machine Learning Engineer
Fully Remote, United States | $200,000 to $230,000 base plus equity and benefits

This is a high impact opportunity to shape how Vision Language Models are applied in real world, production grade systems. You will play a central role in building and scaling VLM driven intelligence that connects edge devices with cloud based reasoning, influencing both technical direction and product outcomes in a fast moving environment.

The Company
They are a technology led organisation building intelligent, connected solutions that blend advanced machine learning with real world operational workflows. Their platform is designed to turn complex visual data into actionable insights at scale. The team brings together expertise across machine learning, computer vision, embedded systems and data science, with a strong focus on building systems that perform reliably in production.

The Role

• Own the design and development of cloud based Vision Language Model pipelines used for large scale labelling and annotation
• Drive decisions on what visual signals, metadata and contextual information are captured from edge devices to maximise VLM performance
• Build and evaluate end to end inference systems, including prompt design, fine tuning strategies and model benchmarking
• Partner closely with embedded systems, computer vision and data science teams to close the loop between devices and cloud intelligence
• Stay at the forefront of the VLM landscape, assessing and integrating commercial and open source models as capabilities evolve

Your Skills and Experience

• Strong commercial experience as a machine learning engineer working with computer vision, LLMs or Vision Language Models
• Hands on experience evaluating, fine tuning or deploying VLMs in production environments
• Deep understanding of how edge constraints such as bandwidth, latency and compute influence model design
• Proficiency with Python, PyTorch and modern cloud based inference and evaluation tooling
• Practical expertise in prompt engineering and model evaluation, with a focus on measurable performance improvements
• Comfortable owning problems end to end and collaborating across hardware and software teams

What They Offer

• Competitive base salary of $200,000 to $230,000 plus equity
• Fully remote working across the United States
• Comprehensive benefits including medical, dental and vision cover
• Flexible paid time off and a strong culture of autonomy and trust
• The opportunity to be a technical leader in the application of Vision Language Models at scale

How to Apply
If you are excited by the challenge of building production grade VLM systems with real world impact, apply now to learn more about this opportunity.

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Principal Data Scientist

Remote | Salary up to $220,000 + 15% bonus

This is an opportunity to step into a senior, high-impact Principal Data Scientist role where you will shape the direction of advanced AI and data science initiatives at scale. You will work on commercially meaningful problems, leveraging cutting-edge techniques including generative AI, while influencing both strategy and delivery across a globally recognised platform.

The Company
They are a well-established, innovation-led organisation focused on delivering data-driven products at scale. With a strong investment in AI and advanced analytics, they partner closely across product, engineering, and design to create impactful, user-focused solutions. Their teams are highly collaborative and operate in a modern, fully remote environment that encourages autonomy and technical excellence.

The Role

• Lead the design and implementation of advanced data science and AI solutions aligned to business objectives
• Provide technical leadership across complex projects, setting direction and best practice for modelling and deployment
• Collaborate with cross-functional stakeholders to identify opportunities and define requirements
• Apply generative AI and other advanced methodologies to solve real-world problems
• Translate technical findings into clear, actionable insights for senior stakeholders
• Oversee project timelines and ensure successful delivery across multiple workstreams

Your Skills and Experience

• Strong commercial experience in data science and machine learning, with recognised expertise in a specialist area
• Deep understanding of production-level AI systems and recent exposure to generative AI techniques
• Proven ability to lead complex projects end to end, from concept through to deployment
• Experience working cross-functionally with product, engineering, or business teams
• Clear and collaborative communication style, with the ability to influence senior stakeholders
• Background in a quantitative or technical field such as Data Science, AI, Mathematics, or similar

What They Offer

• Salary up to $220,000 with a 15% performance bonus
• Fully remote working with flexibility and autonomy
• Opportunity to work on high-impact AI initiatives at scale
• Collaborative, forward-thinking technical environment
• Clear scope for progression into broader technical or strategic leadership roles

How to Apply
If you’re interested in exploring this Principal Data Scientist opportunity, apply now for a confidential discussion.

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Senior AI Engineer, Agentic Systems
Remote (US) $150,000 to $220,000 + Bonus + Equity

This is an opportunity to join an AI-first technology company building sophisticated agentic systems that automate complex business workflows. You’ll play a key role in shaping both customer-facing AI capabilities and the internal engineering practices that enable teams to build faster, smarter, and more effectively.

The Company
They are an innovative software business leveraging advanced AI and autonomous systems to transform how organisations manage complex operational workflows. Their platform combines proprietary intelligence, enterprise data integration, and agent orchestration to deliver highly automated outcomes at scale. With a remote-first culture and a strong engineering focus, they offer an environment where technical expertise has a direct impact on product direction and business growth.

The Role
As a Senior AI Engineer, you will:

• Design and develop agentic workflows, autonomous systems, and AI-powered product features
• Build orchestration frameworks, tool integrations, and multi-step agent capabilities
• Create robust evaluation, monitoring, guardrail, and observability frameworks for production AI systems
• Collaborate with Product teams to translate complex business processes into reliable agent-driven solutions
• Integrate AI workflows with enterprise platforms, data systems, and third-party technologies
• Own the full software development lifecycle from design through deployment and optimisation
• Contribute to architecture decisions and technical strategy across the engineering function
• Champion the effective use of AI-assisted development tools and help establish engineering best practices
• Work closely with a high-performing team to deliver scalable, production-ready solutions

Your Skills & Experience

• Strong commercial software engineering experience with expertise across distributed systems, APIs, and scalable application development
• Proven experience building applications using LLMs, AI agents, orchestration frameworks, or autonomous workflows
• Experience designing and deploying production-grade AI systems with a focus on reliability and performance
• Knowledge of agent tooling, tool use frameworks, MCP, or similar integration approaches
• Ability to work across the full development lifecycle and take ownership of complex technical initiatives
• Strong communication skills and experience collaborating within remote or distributed teams
• Curiosity about emerging AI technologies and a passion for applying them to solve real-world challenges

Desirable experience includes:

• Exposure to marketing technology, advertising technology, media platforms, or customer data ecosystems
• Experience integrating with enterprise data platforms, cloud data warehouses, or third-party APIs
• Familiarity with LangChain or similar agent orchestration frameworks
• Experience evaluating or running local and self-hosted LLM environments

What They Offer

• Competitive base salary
• Equity participation
• Comprehensive benefits package
• Fully remote working across the US
• Access to collaborative office space for those who prefer a hybrid environment
• The opportunity to influence product strategy and engineering standards
• Exposure to cutting-edge AI and agentic system development
• Clear opportunities for professional growth within a rapidly evolving technology environment

How to Apply
If you’re excited by the future of agentic software engineering and want to build AI systems that have a tangible impact, apply today to learn more about this opportunity.

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Machine Learning Engineering Manager
USA Remote $200,000 – $230,000 base + bonus + equity

A high-impact Machine Learning Engineering role focused on building and scaling production systems for real-time decisioning. You will manage a team of 4 and own end-to-end ML pipelines, working on models that directly drive commercial outcomes at scale, as well as contribute to ML research within the AI Lab.

The Company

They are a fast-growing technology business operating in the e-commerce and payments space, processing large volumes of real-time transactions. Machine learning sits at the core of their product, with strong investment in infrastructure and experimentation. Teams own services end to end, enabling engineers to drive meaningful technical impact.

The Role

* Build and deploy production-grade ML models for real-time systems
* Design scalable ML pipelines and infrastructure for high-throughput environments
* Develop offline experimentation and evaluation frameworks
* Improve model performance through statistical methods and feature engineering
* Work with distributed systems and large-scale data processing
* Partner with cross-functional teams to deliver ML solutions aligned to business needs
* Own the full lifecycle from experimentation to production and monitoring

Your Skills & Experience

* Strong commercial experience in Machine Learning Engineering
* Expertise in Python, SQL, and distributed frameworks such as Spark
* Deep understanding of model evaluation, experimentation, and statistics
* Experience building scalable ML systems from first principles
* Team leadership experience

What They Offer

* $200,000 – $240,000 base salary + bonus + equity
* Fully remote working in the US
* Unlimited paid time off and flexible working
* Comprehensive health and financial benefits, including 401k
* Learning budget and clear ownership of high-impact systems

How to Apply

Apply now to explore this Machine Learning Engineering opportunity.

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Principal Software Engineer

Remote (US East Coast preferred) | Up to $300,000 Total Cash Compensation + Equity

A great opportunity to join an early-stage AI software business at a defining point in its growth. As the senior technical leader within a small but rapidly expanding engineering function, you will have significant influence over architecture, engineering standards, product direction, and team development while remaining deeply hands-on in the code.

The Company

They are a profitable AI business helping organisations identify practical, high-impact opportunities for AI adoption and transformation. Their flagship platform combines data, process modelling, and AI technologies to create digital representations of organisations, enabling leaders to make more informed operational and investment decisions.

The Role

This Principal Software Engineer role is best suited to a hands-on technical leader who enjoys building, mentoring, and solving complex engineering challenges.

You will:

• Lead the architecture, development, and scaling of a cloud-native AI platform
• Act as the senior technical contributor across a multi-disciplinary team of software engineers, data engineers, and data scientists
• Drive engineering best practices, software quality, and code review standards
• Build and deploy production-grade AI and LLM-powered applications
• Own technical decision-making across application architecture, infrastructure, and platform scalability
• Partner closely with product and business stakeholders to deliver commercially valuable solutions
• Play a key role in shaping the future engineering organisation as headcount grows

Your Skills & Experience

• Strong commercial experience building software applications in Python
• Experience as a Principal Engineer, Staff Engineer, Technical Lead, Founding Engineer, or similar senior individual contributor role
• Proven track record delivering production AI or LLM-based applications beyond experimentation or proof-of-concept work
• Experience with modern LLM frameworks and orchestration tooling such as LangChain, LangGraph, or similar technologies
• Strong understanding of multi-model AI environments and working with leading foundation model providers
• Experience owning cloud infrastructure and deployment pipelines, ideally within Google Cloud Platform
• Knowledge of services such as Cloud Run, BigQuery, IAM, containerisation, and CI/CD tooling
• Experience working within startup, or other lean engineering environments
• Interest in AI adoption, automation, analytics, or operational transformation projects

What They Offer

• Up to $300,000 total cash compensation including bonus
• High levels of ownership and technical influence
• Opportunity to shape engineering culture, processes, and platform architecture
• Greenfield environment with modern technologies and no legacy estate
• Clear career progression as the engineering organisation scales

How to Apply

If you are a hands-on Principal Software Engineer with strong Python expertise, production LLM experience, and a passion for building and mentoring within a growing AI business, please apply for a confidential discussion.

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