ai and machine larning RECRUITERS in
ATLANTA

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Manager, AI Architecture

Atlanta, GA – Hybrid (3 days per week onsite)

$175,000-$200,000 base salary + annual bonus

THE COMPANY

Our client is a leading global consulting and transformation firm helping enterprise organizations leverage data, analytics, and artificial intelligence to drive measurable business outcomes. Their AI and Data practice combines deep technical expertise with strategic advisory capabilities to deliver scalable, production-ready AI solutions across a range of industries.

This is an opportunity to join a high-performing team at the forefront of enterprise AI, working on complex transformation initiatives that bring generative AI, agentic systems, and advanced analytics into real-world business environments.

RESPONSIBILITIES

• Lead the design and delivery of enterprise AI architecture solutions across client engagements.
• Build and oversee scalable AI platforms, agentic workflows, inference pipelines, and API-driven architectures.
• Partner with client stakeholders, engineering teams, and business leaders to translate requirements into robust technical solutions.
• Drive architectural decisions related to AI governance, security, observability, and production deployment.
• Establish best practices for evaluation-driven development, testing, and AI solution lifecycle management.
• Contribute to reusable frameworks, accelerators, technical standards, and architecture documentation that support broader delivery teams.

SKILLS AND EXPERIENCE

Required:

• 8+ years of experience in software engineering, AI/ML engineering, or AI architecture roles.
• Strong hands-on expertise designing and implementing LLM-based solutions, including RAG architectures, function calling, and AI agents.
• Experience with orchestration frameworks and vector database technologies.
• Deep understanding of cloud-native deployment, monitoring, security, and operational best practices.
• Proven ability to make independent technical decisions and communicate architecture recommendations to technical and non-technical stakeholders.
• Experience designing and delivering production-ready AI solutions within enterprise environments.
• Knowledge of responsible AI principles, including governance, privacy, security, and ethical AI practices.

Preferred:

• Consulting or client-facing delivery experience.
• Experience building reusable AI frameworks, accelerators, or platform capabilities.
• Familiarity with emerging agentic AI architectures and modern AI engineering practices.
• Project leadership and stakeholder management experience.

BENEFITS

• Competitive base salary of $175,000-$200,000.
• Annual performance bonus.
• Exposure to large-scale enterprise AI transformation programs.
• Hybrid working model with a collaborative team environment.
• Ongoing learning and development opportunities within a fast-growing AI practice.
• Opportunity to work with cutting-edge AI, GenAI, and machine learning technologies.

HOW TO APPLY

Please register your interest by sending your CV via the Apply link on this page.

KEY TERMS

Manager AI Architecture | AI Architect | Generative AI | GenAI | Artificial Intelligence | LLM | Large Language Models | RAG | Retrieval Augmented Generation | AI Agents | Agentic AI | Vector Databases | Cloud Architecture | Machine Learning | AI Engineering | Enterprise AI | Solution Architecture | API Development | AI Governance | Consulting | Atlanta Jobs | Hybrid Working

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Lead Data Scientist
Base salary: $140,000 – $150,000

Overview

A leading enterprise organisation is seeking a senior-level Data Scientist to lead the development, validation, and implementation of advanced quantitative models in a highly regulated environment. This role will serve as a technical leader, partnering with business and executive stakeholders to identify financial opportunities, quantify outcomes, and drive data-driven decision making.
The successful candidate will bring deep expertise in risk and financial modelling, strong statistical and mathematical foundations, and the ability to independently deliver complex analytics projects from concept through deployment and governance review.

Key Responsibilities

• Design, develop, validate, and monitor advanced predictive and risk models.
• Analyse large-scale financial, transactional, and customer datasets.
• Apply machine learning and statistical techniques to solve complex business problems.
• Translate model insights into measurable financial impact and business recommendations.
• Lead analytics initiatives from problem definition through implementation and performance tracking.
• Present technical findings and strategic recommendations to senior leadership and executive stakeholders.
• Support model governance activities, regulatory reviews, and external audit processes.
• Collaborate with cross-functional teams to ensure models are aligned with business objectives and compliance requirements.
• Provide technical guidance and mentorship to peers and junior team members.

Required Qualifications

• 8+ years of experience in Data Science, Quantitative Analytics, Risk Analytics, or a related discipline.
• Advanced proficiency in Python and SQL.
• Strong expertise in data modelling, statistical analysis, and quantitative problem solving.
• Experience developing and evaluating gradient boosting and other predictive modelling techniques.
• Proven ability to independently own and drive complex analytical projects.
• Exceptional communication and presentation skills, including experience presenting to executive audiences.
• Demonstrated experience defending models during audits, reviews, or governance assessments.
• Background in financial or risk modelling within a regulated industry.

Required Domain Experience

Candidates should have experience in one or more of the following areas:

• Credit risk modelling
• Financial forecasting and modelling
• Loss estimation and assessment
• Probability of Default (PD) modelling
• Risk scorecard development
• Payment and behavioural modelling
• Credit attribute modelling
• Banking, lending, consumer credit, mortgage, or credit bureau data
• Financial impact analysis
• Risk analytics within regulated financial institutions

Preferred Qualifications

• Bachelor’s degree in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field.
• Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, or a similar quantitative discipline preferred.
• Advanced academic training with significant mathematical and statistical coursework.

Work Model / Location / Engagement Details

• Hybrid work arrangement requiring onsite attendance four days per week (Monday through Thursday).

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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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