Freddie Mac
Risk Management
TechnicalLead,GenAI&AutomationEngineering(RiskEngineering)
Neural analysis suggests this role is
optimal for Senior candidates.
“Technical Lead, GenAI & Automation Engineering (Risk Engineering) at Freddie Mac. Skills: GenAI & Automation Engineering, AI engineering, risk management, LLMs, RAG architectures, Python. design and build AI-driven use cases. agentic workflows”
What You'll Achieve.
Deliver robust, well-tested, and production-ready solutions; ensure high-quality data, outputs, and system performance
Industry & Context.
solve complex business and risk challenges
What They're Looking For.
Must Have
Bachelor’s degree in Computer Science, Engineering, or a related field, 8–10+ years of experience in software engineering, 5+ years of experience in AI/ML or GenAI engineering, proficiency in Python, experience with frameworks such as LangChain or similar, Experience building LLM-based applications, including RAG and prompt engineering, Knowledge of APIs, microservices, and distributed systems in cloud environments (AWS preferred), Experience with MLOps/DataOps pipelines, observability, and monitoring tools, Familiarity with vector databases and modern AI architectures, Experience with LLM evaluation, guardrails, or AI safety mechanisms, Familiarity with AI governance, model risk, or responsible AI frameworks, Experience implementing risk, control, or compliance requirements in technical systems, Experience with platforms such as AWS Bedrock, Azure OpenAI, and GitHub Copilot
Nice to Have
advanced degree preferred
What You'll Do.
design and build AI-driven use cases
and risk intelligence directly into GenAI systems
lead the development of production-grade GenAI solutions
design and implement scalable GenAI applications
building and optimizing RAG pipelines
vector search solutions
multi-modal AI integrations
develop Python-based microservices and APIs
lead automation framework design
ensure efficient deployment and high system performance
embedding risk and control mechanisms directly into GenAI workflows
translating regulatory requirements into scalable code
design feature engineering and data pipelines
establish feedback loops for continuous improvement
How You'll Work.
Team & Collaboration
partnering with Risk, Security, and Governance teams; collaborate with cross-functional teams; Work effectively across engineering, product, and risk teams
Full Job Description
At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. **Position Overview** We are seeking a highly experienced Technical Lead in GenAI & Automation Engineering to design and build AI-driven use cases, agentic workflows, and automation solutions that solve complex business and risk challenges. This role sits at the intersection of AI engineering and risk management, focusing on embedding controls, governance, and risk intelligence directly into GenAI systems (“control as code”). You will lead the development of production-grade GenAI solutions, leveraging technologies such as LLMs, RAG architectures, vector databases, and modern cloud-native frameworks, while ensuring scalability, reliability, and responsible AI practices. ## Our Impact At Freddie Mac, our mission of Making Home Possible drives everything we do. As we advance into an AI-powered future, we are transforming how risk management is designed, implemented, and scaled—moving from manual processes to intelligent, automated, and embedded risk capabilities. This role is part of a next-generation initiative to reimagine risk management through GenAI and automation, where controls are engineered into systems, not just documented. ## Your Impact In this role, you will design and implement scalable GenAI applications, AI agents, and agentic workflows to solve complex business challenges, while building and optimizing RAG pipelines, vector search solutions, and multi-modal AI integrations. You will develop Python-based microservices and APIs, lead automation framework design, and ensure efficient deployment and high system performance. A key differentiator is embedding risk and control mechanisms directly into GenAI workflows, translating regulatory requirements into scalable c
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