Jobs in the United States

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Technology Strategy Technical Lead

McLean, VA, United States

This position has an annualized market-based salary range of $149,000 - $223,000 and is eligible to participate in the annual incentive program.

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Job details

Pay: This position has an annualized market-based salary range of $149,000 - $223,000 and is eligible to participate in the annual incentive program.
Experience: 8-10+ years of software, data, or machine learning engineering experience, including 3+ years providing technical leadership for complex engineering teams or initiatives
Posting language: English
Posted: Nov 9, 2026

Original 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:

Do you want your technical leadership to help shape how an entire enterprise puts generative AI to work, safely, at scale, and for real impact? At Freddie Mac, our mission of Making Home Possible is at the core of everything we do, and our Corporate Technology Strategy team is building FredAI, our internal enterprise GenAI platform and portfolio of AI-enabled products. We're searching for a hands-on, highly experienced Technical Lead to guide solution design and engineering delivery, turning cutting-edge foundation models into reliable, measurable business outcomes. Apply now and learn why there's #MoreAtFreddieMac!

Our Impact:

We build FredAI, the secure, scalable platform and reusable services that bring generative AI capabilities - including the company's internal chatbot and AI-enabled products - to teams across the enterprise.
We translate the Freddie Mac CIO vision for GenAI into an executable engineering roadmap, setting the reference architectures, standards, and shared frameworks that let multiple product teams deliver consistently and responsibly.
We partner across Architecture, Cybersecurity, Data, Model Risk, and Cloud Engineering to ensure every solution meets enterprise expectations for identity, data protection, auditability, resiliency, and responsible AI.

Your Impact:

In this role, you will be an integral part of our GenAI engineering team and will be expected to:

Provide hands-on technical leadership for the architecture, design, and delivery of FredAI capabilities, building 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 that accelerate delivery across multiple product teams.
Implement rigorous evaluation, testing, and LLMOps practices - 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, fostering a culture of ownership, engineering discipline, and experimentation.
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.

Qualifications:

8-10+ years of software, data, or machine learning engineering experience, including 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 (advanced degree preferred)
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 (Python, TypeScript/JavaScript, or Java; APIs, microservices, containers, distributed systems, CI/CD, IaC)
Hands-on knowledge of LLM application patterns - 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

Keys to Success in this Role:

A builder's mindset: you enjoy solving the hardest engineering problems hands-on while guiding others through sound technical decisions
A credible technical influencer who can align engineering, security, data, risk, and business partners around a shared solution design.
Comfortable operating in the space of "no longer" and "not yet" - translating fast-moving GenAI advances into practical, governed capabilities
Calm under pressure, with strong operational discipline and a bias toward measurable outcomes
A curious, continuous learner who stays current on emerging AI technologies - and a great teammate with a sense of humor

Current Freddie Mac employees please apply through the internal career site.

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.

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 $149,000 - $223,000 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.

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More about this job

Skills

Leadership
Chatbot
Cybersecurity
Data protection
CI/CD
Incident response
Cost management
Coaching
Problem solving
Machine learning
Computer science
ML
Python
TypeScript
JavaScript
Oracle Java
Microservices
Infrastructure as code

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