Position OverviewWe 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.
Your ImpactIn 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 code, and partnering with Risk, Security, and Governance teams. You will also design feature engineering and data pipelines, establish feedback loops for continuous improvement, and collaborate with cross-functional teams while providing technical leadership. Success in this role requires engineering excellence, technical depth in Python and AI/ML frameworks, data readiness, a risk-aware mindset, and a commitment to innovation in emerging AI technologies.
Qualifications- Bachelor's degree in Computer Science, Engineering, or a related field (advanced degree preferred)
- 8-10+ years of experience in software engineering
- 5+ years of experience in AI/ML or GenAI engineering
- Strong proficiency in Python and 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
Keys to Success in the Role- Technical Proficiency: Strong Python skills and ability to build scalable microservices
- Quality & Reliability: Deliver robust, well-tested, and production-ready solutions
- Learning Agility: Continuously develop skills in GenAI and emerging technologies
- Collaboration: Work effectively across engineering, product, and risk teams
- Attention to Detail: Ensure high-quality data, outputs, and system performance
Current Freddie Mac employees please apply through the internal career site.Time-type:Full time
FLSA Status:Exempt
Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.
This position has an annualized market-based salary range of $146,000 - $218,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.
