Technical Lead, GenAI & Automation Engineering (Risk Engineering)

Freddie Mac•McLean, VA

1d•$146,000 - $218,000

About The Position

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.

Requirements

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

Nice To Haves

Deliver robust, well-tested, and production-ready solutions
Continuously develop skills in GenAI and emerging technologies
Work effectively across engineering, product, and risk teams
Ensure high-quality data, outputs, and system performance

Responsibilities

Design and implement scalable GenAI applications, AI agents, and agentic workflows to solve complex business challenges.
Build and optimize RAG pipelines, vector search solutions, and multi-modal AI integrations.
Develop Python-based microservices and APIs.
Lead automation framework design.
Ensure efficient deployment and high system performance.
Embed risk and control mechanisms directly into GenAI workflows, translating regulatory requirements into scalable code.
Partner with Risk, Security, and Governance teams.
Design feature engineering and data pipelines.
Establish feedback loops for continuous improvement.
Collaborate with cross-functional teams.
Provide technical leadership.