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Title: Senior AI Engineer

Location: Remote, United States

Compensation: Up to $240,000 + Equity

We’re partnered with a high-growth, mission-driven SaaS company transforming how businesses build and maintain trust, with AI at the core of their next phase of innovation. The platform is redefining how critical enterprise workflows are automated, particularly in areas where reliability, auditability, and security are essential.

This is a high-impact role where you will help define how AI is architected across the company. You won’t just be building features. You’ll make foundational decisions around systems, evaluation, and long-term technical direction, working across LLMs, retrieval systems, and agent-based workflows in production environments.

What You’ll Do

• Design and own production AI systems end-to-end, including LLM pipelines, retrieval systems, and orchestration layers
• Build and scale RAG systems, reranking pipelines, and vector-based search infrastructure
• Define evaluation frameworks to measure retrieval quality, reasoning accuracy, and system performance
• Analyze production behavior, identify failure modes, and drive improvements based on data
• Make key architectural decisions across model infrastructure, tooling, and workflows
• Partner closely with product, platform, and domain teams to translate complex requirements into scalable systems
• Lead best practices for building reliable, observable, and cost-efficient AI systems

Requirements

• 6+ years of software engineering experience, including 3+ years working on ML or AI systems
• Proven experience owning and deploying production LLM systems
• Strong background in RAG, embeddings, reranking, and vector databases (e.g., Pinecone, FAISS, Chroma)
• Experience designing evaluation systems and improving models through quantitative analysis
• Strong Python skills, with solid software engineering fundamentals
• Experience making architectural decisions that influence team or org direction
• Strong understanding of production systems, including reliability, observability, and cost tradeoffs
• Ability to break down ambiguous problems and operate with a high degree of ownership
• Clear communication skills and experience working cross-functionally

Nice to Have

• Experience in regulated domains such as compliance or security
• Familiarity with data platforms or analytics tooling
• Experience with orchestration frameworks (e.g., Temporal, Airflow)
• Exposure to LLM evaluation platforms or tooling
• Contributions to open source, research, or technical communities

If you’re interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

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Title: Staff AI Engineer

Location: Remote, United States

Compensation: Up to $280,000 + Equity

We’re partnered with a high-growth, mission-driven SaaS company transforming how businesses build and maintain trust, with AI at the core of their next phase of innovation. The platform is redefining how critical enterprise workflows are automated, particularly in areas where reliability, auditability, and security are essential.

This is a high-impact role where you will help define how AI is architected across the company. You won’t just be building features. You’ll make foundational decisions around systems, evaluation, and long-term technical direction, working across LLMs, retrieval systems, and agent-based workflows in production environments.

What You’ll Do

• Design and own production AI systems end-to-end, including LLM pipelines, retrieval systems, and orchestration layers
• Build and scale RAG systems, reranking pipelines, and vector-based search infrastructure
• Define evaluation frameworks to measure retrieval quality, reasoning accuracy, and system performance
• Analyze production behavior, identify failure modes, and drive improvements based on data
• Make key architectural decisions across model infrastructure, tooling, and workflows
• Partner closely with product, platform, and domain teams to translate complex requirements into scalable systems
• Lead best practices for building reliable, observable, and cost-efficient AI systems

Requirements

• 10+ years of software engineering experience, including 3+ years working on ML or AI systems
• Proven experience owning and deploying production LLM systems
• Strong background in RAG, embeddings, reranking, and vector databases (e.g., Pinecone, FAISS, Chroma)
• Experience designing evaluation systems and improving models through quantitative analysis
• Strong Python skills, with solid software engineering fundamentals
• Experience making architectural decisions that influence team or org direction
• Strong understanding of production systems, including reliability, observability, and cost tradeoffs
• Ability to break down ambiguous problems and operate with a high degree of ownership
• Clear communication skills and experience working cross-functionally

Nice to Have

• Experience in regulated domains such as compliance or security
• Familiarity with data platforms or analytics tooling
• Experience with orchestration frameworks (e.g., Temporal, Airflow)
• Exposure to LLM evaluation platforms or tooling
• Contributions to open source, research, or technical communities

If you’re interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

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Forward Deployed Senior Data Scientist

Salary: $175,000+ (Depending on Experience)

Locations: Remote (with 25% travel)

THE COMPANY

A high‑growth, mission‑focused technology organisation is expanding its advanced analytics and AI function. Operating in a complex, data‑rich environment, the team builds scalable, high‑impact AI systems that support critical decision‑making and deliver tangible operational value. The environment is fast‑paced, innovative, and ideally suited to someone who thrives in high‑autonomy, high‑impact roles.

THE ROLE

As a Forward Deployed Senior Data Scientist, you will work directly with stakeholders to translate complex problems into deployable AI solutions. You’ll use a combination of proprietary and commercial datasets to uncover insights, build models, and deploy production‑ready systems that support strategic decision‑making.

This role blends hands‑on data science, AI engineering, rapid prototyping, and end‑to‑end delivery ideal for someone who is highly analytical, scrappy, and passionate about solving complex technical challenges with real‑world impact.

KEY RESPONSIBILITIES

• Build advanced AI/ML/DS models and systems tailored to high‑value operational challenges
• Develop new AI‑driven technology stacks designed for specific customer use cases
• Lead end‑to‑end delivery of AI projects, from scoping to production deployment
• Partner with research, engineering, and software teams to deliver robust AI products
• Define architectural standards and project roadmaps for scalable AI systems
• Create evaluation frameworks for AI deployments, including performance, reliability, and observability
• Mentor junior team members and help shape a culture of excellence and innovation
• Stay current with emerging techniques in AI, LLMs, and agentic systems; drive adoption of best practices
• Build agentic AI systems leveraging reasoning frameworks and orchestrators
• Act as a technical leader, translating high‑level objectives into actionable technical plans

EXPERIENCE REQUIRED

• Extensive experience designing, developing, and delivering AI/ML solutions end‑to‑end
• Strong software and data science fundamentals (Python essential)
• Experience building production‑grade AI systems and integrating them into customer environments
• Ability to collaborate across research, engineering, and product teams
• Experience working with large‑scale datasets and cloud‑based ML deployments
• Strong organisational skills and the ability to communicate complex ideas clearly
• Proven ability to operate independently in fast‑moving environments and manage competing priorities
• Passion for rapid prototyping, experimentation, and building high‑impact solutions

DESIRABLE EXPERIENCE

• Publications in top AI/ML/NLP or decision science venues
• Experience developing evaluation systems for LLMs or agentic models
• Experience with fine‑tuning, post‑training, or advanced model adaptation
• Familiarity with MLOps, monitoring, deployment, and large‑scale model management
• Track record of converting research prototypes into production systems

THE OFFER

• Competitive compensation (around $175,000 base depending on experience)
• Opportunity to work on deeply impactful, high‑scale AI challenges
• High degree of autonomy, technical ownership, and end‑to‑end influence
• A fast‑paced, innovation‑driven environment with strong technical peers
• Exposure to cutting‑edge modelling, LLMs, and agentic system development

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Senior AI Engineer

$175,000 Base Salary

Location: Pittsburgh, PA (Onsite)

THE COMPANY

This organisation operates within a highly secure, mission‑critical environment and is scaling its advanced AI engineering function. They focus on building intelligent, autonomous systems that streamline complex operational workflows and support high‑stakes decision‑making. The work is deeply technical, fast‑moving, and has genuine real‑world impact.

THE ROLE

You’ll be joining a small, high‑calibre engineering team focused on next‑generation agentic AI. The position involves building multi‑agent architectures, long‑horizon planning systems, and robust tools that enable agents to operate reliably at scale.

The ideal candidate loves solving ambiguous technical problems, has shipped LLM‑driven systems end‑to‑end, and thrives in a startup‑style environment.

KEY RESPONSIBILITIES

• Design and build advanced agent‑based systems with planning, routing, memory, and tool‑use capabilities
• Develop modular “skills” and components that integrate with internal services and data pipelines
• Own architectural standards, scalability, and system reliability
• Implement evaluation frameworks, behavioural telemetry, and regression testing
• Partner closely with product and implementation teams to address complex operational challenges

EXPERIENCE REQUIRED

• 5+ years building production ML or LLM-powered systems
• Strong Python engineering background
• Hands‑on experience with LLM integration, agent frameworks, and cloud infrastructure (AWS preferred)
• Proven ability to build systems end‑to‑end in high‑ambiguity, high‑impact environments
• Familiarity with Git, CI/CD, and modern engineering best practices

DESIRABLE EXPERIENCE

• Multi‑agent coordination, tool orchestration, or agentic system design
• Exposure to startup or rapid‑growth engineering teams
• Eligibility for work in secure environments
• Experience with front‑end frameworks (React/Next.js) is a bonus

THE OFFER

• $175,000 base salary
• High‑impact projects with substantial autonomy
• Chance to shape a new generation of agentic AI capabilities
• Work with exceptional technical peers in a deeply mission‑driven setting

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Director of AI

US REMOTE

Up to $300,000 + Bonus

A global leader in digital learning and education technology is seeking a Director of AI to spearhead the development and delivery of advanced, AI‑powered learning experiences. This is a high‑visibility, high‑impact role driving innovation across millions of users worldwide.

You’ll lead a talented team of AI researchers and data scientists, setting the strategy and technical direction for next‑gen learning products, assessment solutions, and intelligent content systems, all within a collaborative, mission‑driven environment.

THE ROLE

As Director of AI, you will:

• Lead a team of AI/ML and GenAI specialists delivering cutting‑edge models and intelligent learning solutions
• Work cross‑functionally with Product, Engineering, Research, and Innovation teams to embed AI into core digital products
• Shape the AI roadmap for interactive learning, personalised assessment, and content creation technology
• Oversee technical design, model development, evaluation, and deployment for large‑scale, production‑level use
• Represent the AI function internally, influencing senior leaders and driving adoption of scalable AI capabilities
• Build a culture of experimentation, scientific rigour, and innovation across the AI team

REQUIREMENTS

You will bring:

• A strong track record leading AI/ML research or applied data science teams
• Deep expertise in Generative AI, LLMs, NLP, and modern machine‑learning techniques
• Experience building AI solutions that operate at scale and integrate into consumer‑facing digital products
• Exceptional communication skills, with the ability to translate complex technical concepts to non‑technical stakeholders
• Strategic leadership ability balanced with hands‑on technical credibility
• Experience hiring, mentoring, and growing high‑performing AI teams

Preferred but not essential:

• Experience in EdTech, digital content, learning technology, or adjacent industries
• Delivery of advanced AI features into production environments with large user bases

THE BENEFITS

• Competitive base salary + annual bonus
• Opportunity to lead AI strategy at a global scale and shape the future of digital learning
• Work with cutting‑edge technology to solve meaningful, mission‑driven problems
• Hybrid working with a major hub in New York
• Collaborative, supportive culture with strong investment in long‑term innovation

If you’re excited by the idea of building next‑generation AI systems that will transform how millions learn and engage with digital education, apply now to discuss this confidential opportunity.

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Staff AI Engineer

(Hands‑on, LLM Platforms, Technical Lead)

Location: New York
Working model: On‑site
Package: Competitive base + performance‑linked upside

The Opportunity

An established, technology‑driven organisation is building a central AI engineering capability to support complex, data‑intensive decision‑making across the business.

This is a high‑impact individual contributor role for a Senior AI Engineer who enjoys operating close to the commercial core. You’ll take ownership of critical AI systems from architecture through to deployment, working within a small, trusted technical group with direct access to senior stakeholders.

The environment suits someone who thrives in low‑bureaucracy, high‑autonomy settings, where AI is expected to deliver real, measurable value, not experiments for experimentation’s sake.

The Role

You will act as the technical lead for advanced AI tooling, owning system design and delivery across a range of internal use cases.

Responsibilities include:

• Designing and building LLM‑based applications, including retrieval‑augmented generation and agent‑style workflows
• Owning end‑to‑end system architecture, performance, and scalability
• Developing AI tools to support research, monitoring, knowledge discovery, and decision support
• Establishing evaluation and quality frameworks to ensure AI outputs meet high reliability standards
• Reviewing code, setting engineering standards, and supporting the development of other engineers
• Partnering closely with non‑technical users to translate complex workflows into intuitive AI products
• Assessing third‑party tooling and platforms where appropriate

This is a deeply hands‑on role with real ownership.

What We’re Looking For

Core requirements:

• Strong software engineering background (Python preferred)
• Proven experience building production AI systems, particularly modern LLM applications
• Solid understanding of:
  • Prompt design and iteration
  • Embedding pipelines and vector databases
  • RAG architectures and tool‑use patterns
  • Model evaluation and monitoring
• Experience deploying AI products used by non‑technical stakeholders
• Comfortable setting technical direction while remaining a builder

Nice to have:

• Exposure to complex analytical or commercial domains
• Experience working in small, senior engineering teams
• Background in cloud‑native environments

Why Join?

• Ownership of mission‑critical AI systems
• Direct visibility of impact, your work will be used day‑to‑day
• Modern AI stack with freedom to make technical decisions
• Long‑term scope to shape and grow the AI engineering function

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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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STAFF AI ENGINEER

Palo Alto, California, United States (On-site / Hybrid)

The Role

We’re hiring a Staff AI Engineer to build and scale production-grade GenAI systems powering enterprise AI applications.

This is a high-ownership IC role focused on LLM systems, agent frameworks, and production AI infrastructure. You’ll take foundation models and turn them into scalable, reliable systems used for copilots, automation, and internal workflows.

You’ll work across architecture and implementation in a fast-moving environment with rapid production iteration.

What You’ll Build

• Production LLM-powered services and applications
• Enterprise copilots and conversational AI systems
• Text-to-code and natural language SQL systems
• Agent frameworks and tool-using AI systems
• Workflow automation powered by foundation models
• API layers for LLM integration across systems
• Scalable GenAI infrastructure and deployments
• CI/CD pipelines for AI services

What You Bring

• 8-12+ years software or ML engineering experience
• Strong experience building production LLM or ML systems
• Deep understanding of foundation models and LLM APIs
• Strong backend and distributed systems experience
• Experience with AWS production environments
• Kubernetes / containerized deployment experience
• Strong systems thinking (latency, scaling, reliability trade-offs)

Strong Preference For

• ML engineering background over traditional full-stack
• Experience building GenAI or agentic systems in production
• Strong analytical background (PhD-level NLP/CV a plus)

Why This Role

• Build and scale core GenAI infrastructure with real impact
• High ownership from architecture through production
• Fast iteration cycles and strong technical autonomy
• High visibility with senior technical leadership
• Opportunity to shape foundational AI systems at scale

• Opportunity to shape foundational AI systems at scale

To Apply for this Job Click Here

To Apply for this Job Click Here

STAFF AI ENGINEER

New York, United States (On-site / Hybrid)

The Role

We’re hiring a Staff AI Engineer to build and scale production-grade GenAI systems powering enterprise AI applications.

This is a high-ownership IC role focused on LLM systems, agent frameworks, and production AI infrastructure. You’ll turn foundation models into reliable, scalable systems that power copilots, automation, and internal AI workflows.

You’ll operate across architecture and implementation with fast iteration from idea to production.

What You’ll Build

• Production LLM-powered services and applications
• Enterprise copilots and chat-based systems
• Text-to-code and natural language SQL interfaces
• Agent frameworks and tool-using AI systems
• Workflow automation powered by foundation models
• API layers for LLM integration across systems
• Scalable, secure GenAI deployments
• CI/CD pipelines for AI services

What You Bring

• 8-12+ years software or ML engineering experience
• Strong experience building production LLM or ML systems
• Deep understanding of foundation models and LLM APIs
• Strong backend and distributed systems experience
• Experience with AWS production environments
• Kubernetes / containerized deployment experience
• Strong systems thinking (latency, scaling, reliability trade-offs)

Strong Preference For

• ML engineering background over traditional full-stack
• Experience building GenAI or agentic systems in production
• Strong analytical background (PhD-level NLP/CV a plus)

Why This Role

• Build foundational GenAI systems with real enterprise impact
• High ownership across architecture and execution
• Fast iteration cycles from idea to production
• High visibility and technical influence
• Opportunity to shape core AI infrastructure

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