Gen AI Engineering Manager

Freddie Mac • McLean, VA

76d • $153,000 - $229,000

About The Position

Freddie Mac is seeking a visionary Gen AI Engineering Manager to architect and deliver next-generation GenAI applications, agentic workflows, and AI-powered platforms. You will lead a cross-functional team of data scientists and full stack engineers to address diverse and complex business use cases. Your role combines hands-on technical leadership in scalable AI agent design, cutting-edge model development, production-grade deployment, and collaborative full-stack solution delivery. You will champion flawless execution, drive strategic innovation, master stakeholder engagement, and build an agentic, high-performance engineering culture.

Requirements

• Bachelor's in computer science, Artificial Intelligence (AI), Data Science, or related field.
• Master's in computer science or advanced studies preferred.
• 8+ years of experience in Software Engineering with 5 years in data science, 1-2 years in applied GenAI or LLM-based solutions.
• 2+ years of leadership experience.
• Demonstrated experience leading cross-functional agile teams combining data scientists and full stack engineers.
• Deep expertise in prompt engineering, fine-tuning, RAG, Graph RAG, vector databases (AWS Knowledgebase, Elastic), and multi-modal models.
• Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow, Kubeflow on EKS).
• Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).
• Deep understanding of Gen AI system patterns, architectural best practices, and evaluation frameworks for bias mitigation and safety.
• Experience with embedding models, vector stores, multimodal data pipelines, and production-grade validation.
• Excellent communication skills; ability to translate technical concepts for non-technical stakeholders.

Nice To Haves

• Experience in regulated financial environments with compliance automation.
• Prior work implementing agentic workflows and AI-powered enterprise platforms.

Responsibilities

• Collaborate with business stakeholders to identify and incubate innovative ideas by leveraging data science and GenAI experimentation and research.
• Rapidly prototype solutions to validate hypotheses and quantify business impact.
• Lead the development of Minimum Viable Products (MVPs) based on validated experiments, ensuring the MVP delivers tangible value and is architected for scalability and compliance.
• Drive the transition from MVP to scalable, production-ready GenAI solutions.
• Enforce best practices for code quality, validation, security, and operational excellence.
• Architect and implement scalable AI agents, agentic workflows, and GenAI applications tailored for Freddie Mac’s most complex business challenges.
• Develop, fine-tune, and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives.
• Design and deploy Retrieval-Augmented Generation (RAG) and GraphRAG solutions using vector databases and enterprise knowledge bases.
• Curate enterprise data using connectors integrated with AWS Bedrock's Knowledge Base/Elastic to support robust knowledge retrieval.
• Implement solutions leveraging Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication patterns.
• Build and maintain Jupyter-based notebooks using platforms such as SageMaker and MLFlow/Kubeflow on Kubernetes (EKS).
• Partner with UI engineers, microservice developers, designers, and data engineers to deliver seamless, full-stack GenAI experiences.
• Integrate GenAI solutions with enterprise platforms using API-based methods and standardized GenAI patterns.
• Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production-ready deployment.
• Design and build robust ingestion pipelines to extract, chunk, enrich, and anonymize data from PDFs, video, and audio for LLM-powered workflows.
• Orchestrate multi-modal pipelines using scalable frameworks for automated ETL/ELT workflows on unstructured media.
• Implement embeddings mapping media content to vector representations and integrate with vector stores to support advanced RAG architectures.
• Establish agile, empirically driven SDLC and manage delivery metrics.
• Enforce a rigorous 'Definition of Done' for code review, automated security/compliance scans, unit testing, QA validation, and deployment.
• Integrate internal platforms to automate compliance and reduce manual toil.
• Drive predictable engineering flow: story pointing, WIP management, epic deconstruction for AI enablement.
• Lead blameless retrospectives and leverage AI tools for continuous improvement.
• Track and visualize key metrics (DORA, lead time, deployment frequency, uptime).
• Identify and champion technology-driven opportunities (GenAI, ML, cloud, data platforms).
• Build business cases that quantify ROI, TCO, and measurable impact.
• Maintain external focus on industry trends and competitive landscape.
• Collaborate with Risk, Compliance, and InfoSec to innovate safely.
• Set quarterly OKRs and prioritize using a portfolio approach.
• Present quarterly 'State of the Union' and connect stories to strategy.
• Proactively communicate risks, changes, and options to business, technology, and compliance partners.
• Use documentation for clarity and alignment; leverage AI tooling for communication.
• Partner with product and business stakeholders to present crisp options and trade-offs.
• Treat dependencies as contracts and create shared goals for cross-functional initiatives.
• Proactively address compliance and build enablement tooling.
• Foster an agentic, psychologically safe team culture.
• Set explicit expectations and manage performance with structured feedback.
• Conduct growth-focused 1-on-1s and create opportunities for ownership and development.
• Lead hiring and onboarding with clear job descriptions and structured 30-60-90 day plans.

Benefits

• Competitive compensation and market-leading benefit programs.
• Annual incentive program eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees