Technology Strategy Technical Lead

Freddie Mac•McLean, VA

About The Position

Freddie Mac’s Corporate Technology Strategy team builds FredAI, its secure, scalable internal generative AI platform and portfolio of AI-enabled products. The Technical Lead provides hands-on technical leadership for solution design and engineering delivery, turning foundation models into reliable, measurable business outcomes across the enterprise. The role helps translate the CIO’s GenAI vision into engineering roadmaps, reference architectures, standards, and shared frameworks so product teams can deliver consistently and responsibly. The position partners with Architecture, Cybersecurity, Data, Model Risk, Cloud Engineering, and other teams to ensure solutions meet enterprise expectations for identity, data protection, auditability, resiliency, and responsible AI. It provides technical direction and mentoring while owning technical and product-quality outcomes, including availability, latency, throughput, task completion, developer productivity, and cost per successful outcome. This is a full-time, exempt position with an annualized market-based salary range of $149,000–$223,000. It is eligible for participation in the annual incentive program. The final offer depends on factors including responsibilities, experience, skills, internal pay equity, and other qualifications. Freddie Mac describes its total rewards package as comprehensive and provides information about benefit programs on its Careers site.

Requirements

8–10+ years of software, data, or machine learning engineering experience.
At least 3 years providing technical leadership for complex engineering teams or initiatives.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent experience.
Proven experience designing and delivering production GenAI or AI/ML systems at enterprise scale, with recent hands-on coding and technical design experience.
Strong proficiency in modern cloud-native engineering using Python, TypeScript/JavaScript, or Java, and experience with APIs, microservices, containers, distributed systems, CI/CD, and infrastructure as code.
Hands-on knowledge of LLM application patterns, including prompting, RAG, embeddings, vector search, orchestration, tool calling, agents, structured outputs, and model evaluation.
Experience designing for security, privacy, identity, data governance, resiliency, auditability, and responsible AI in a regulated enterprise environment.

Nice To Haves

Advanced degree preferred.
Builder’s mindset and enjoyment of hands-on engineering problem solving while guiding others in technical decisions.
Ability to influence and align engineering, security, data, risk, and business partners around shared solution designs.
Comfort translating fast-moving GenAI advances into practical, governed capabilities.
Calm under pressure, operational discipline, and a bias toward measurable outcomes.
Curiosity and continuous learning about emerging AI technologies; collaborative approach and sense of humor.

Responsibilities

Provide hands-on technical leadership for the architecture, design, and delivery of FredAI capabilities and production GenAI applications using foundation models, RAG, embeddings, vector search, orchestration, tool calling, and agentic workflows.
Design and implement reusable reference architectures, SDKs, shared services, APIs, and integration patterns to accelerate delivery across product teams.
Implement evaluation, testing, and LLMOps practices, including offline benchmarks, regression suites, groundedness and hallucination measures, CI/CD, versioning, observability, tracing, incident response, and rollback.
Engineer secure, permission-aware solutions that enforce identity, entitlements, data boundaries, privacy, human approvals, audit logging, and responsible AI policies.
Define model and platform integration patterns, including model selection and routing, structured outputs, caching, rate limiting, fallback strategies, token budgets, circuit-breaker controls, and cost management.
Partner with cloud, platform, data, and security teams, and with the GenAI Program Manager, to integrate GenAI services with enterprise systems, translate business needs into governed technical solutions, and resolve cross-team engineering dependencies.
Provide technical direction, code and design reviews, mentoring, and hands-on problem solving for GenAI, software, platform, and quality engineers.
Own technical and product-quality outcomes, including availability, latency, throughput, task completion, developer productivity, and cost per successful outcome, and drive corrective actions when targets are not met.