Freddie Mac · 2 days ago
Gen AI Engineering Manager
McLean, VA
Full-time
Onsite
Senior Level, Lead/Staff
$153K/yr - $229K/yr
8+ years expFreddie Mac is a leading organization focused on making home possible for millions of families. They are seeking a Gen AI Engineering Manager to lead a team in architecting and delivering next-generation GenAI applications and solutions, driving innovation and excellence in AI technology deployment.
FinanceFinancial ServicesRisk Management
Responsibilities
Collaborate with business stakeholders to identify and incubate innovative ideas by leveraging data science and GenAI experimentation and research
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
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, leveraging semantic chunking and privacy best practices
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' (code review, automated security/compliance scans, unit testing>80>80coverage, QA validation, 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 (Enablement vs. Targeted Solutions)
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 (OKRs) 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 (SBI model)
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
Qualification
Required
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 yrs. in data science, 1-2 yrs. in applied GenAI or LLM-based solutions
2+ yrs. 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
Preferred
Experience in regulated financial environments with compliance automation
Prior work implementing agentic workflows and AI-powered enterprise platforms
Benefits
Competitive compensation
Market-leading benefit programs
Eligible to participate in the annual incentive program
Company
Freddie Mac
Freddie Mac is a public government-sponsored enterprise that provides mortgage capital to lenders.
5001-10000 employees
H1B Sponsorship
Freddie Mac has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (181)
2024 (119)
2023 (100)
2022 (134)
2021 (112)
2020 (71)
Funding
Current Stage
Public CompanyTotal Funding
$3.58BKey Investors
DLP Capital
2025-12-30Post Ipo Debt· $108.4M
2025-10-28Post Ipo Debt· $343.2M
2025-09-09Post Ipo Debt· $707M
Leadership Team
Dennis G. Hermonstyne
Senior Vice President and Chief Compliance Officer
Peter Lillestolen
Vice President - MF Production and Sales, Targeted Affordable Housing
Recent News
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