Agile Development Sr Tech Lead (Gen AI Data Scientist)

At Freddie Mac our mission of Making Home Possible is what motivates us and its 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:

As theAgile Dev Lead Sr Tech Lead (Gen AI Scientist) you will lead the design and development of advanced Generative AI solutions including AI Agents Agentic Workflows and Gen AI Applications that tackle complex business challenges. This hands-on role demands deep expertise in LLMs multi-modal AI prompt engineering and cloud-native GenAI (CI/CD) deployments as well as the ability to shape and implement enterprise-grade Gen AI systems as both a technical thought leader.

Our Impact:

Our team is at the forefront of applying cutting-edge AI technologiessuch as Agentic AI Retrieval-Augmented Generation (RAG) multi-modal processing and advanced model orchestrationto solve real-world business problems. By architecting scalable robust and secure AI solutions we:

• Enable the organization to automate and enhance decision-making processes.

• Accelerate innovation through intelligent data-driven applications.

• Establish best practices for deploying AI safely and ethically at enterprise scale.

• Foster a culture of collaboration technical excellence and continuous learning.

Your Impact:

• Architect and implement scalable AI Agents Agentic Workflows and GenAI applications to address diverse and complex business use cases.

• Develop fine-tune and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic) Azure OpenAI and open-source alternatives.

• Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.

• Curate enterprise data using connectors integrated with AWS Bedrocks Knowledge Base/Elastic

• Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication.

• Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS)

• Deploy MCP services using CI/CD pipelines (GenAI Ops)

• Collaborate with cross-functional teams of UI and microservice engineers designers and data engineers to build full-stack Gen AI experiences.

• Integrate GenAI solutions with enterprise platforms via API-based methods and GenAI standardized patterns.

• Establish and enforce validation procedures with Evaluation Frameworks bias mitigation safety protocols and guardrails for production-ready deployment.

• Design & build robust ingestion pipelines that extract chunk enrich and anonymize data from PDFs video and audio sources for use in LLM-powered workflowsleveraging best practices like semantic chunking and privacy controls

• Orchestrate multimodal pipelines** using scalable frameworks (e.g. Apache Spark PySpark) for automated ETL/ELT workflows appropriate for unstructured media

• Implement embeddings drivesmap media content to vector representations using embedding models and integrate with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas) to support RAG architectures

Qualifications:

• Bachelor of science and/or Masters of Science. Advanced degree/ sutudies in AI/Data Science.

• 10 years of experience in AI/ML with 3 years in applied GenAI or LLM-based solutions.

• Deep expertise in prompt engineering fine-tuning RAG GraphRAG vector databases (e.g. AWS KnowledgeBase / Elastic) and multi-modal models.

• Proven experience with cloud-native AI development (AWS SageMaker Bedrock MLFlow on EKS).

• Strong programming skills in Python and ML libraries (Transformers LangChain etc.).

• Deep understanding of Gen AI system patterns and architectural best practices Evaluation Frameworks

• Demonstrated ability to work in cross-functional agile teams.

Keys to Success in this Role:

Demonstrate Deep Technical Mastery

• Advanced proficiency in GenAI concepts LLMs multimodal AI and cloud-native ML workflows.

• Strong programming skills and hands-on experience with tools such as Python SageMaker Bedrock MLFlow and Kubernetes.

Architect Scalable and Robust Solutions

• Ability to design and deploy AI systems that are secure scalable and maintainable.

• Expertise in building RAG architectures data ingestion pipelines and embedding-driven retrieval systems.

Collaborate Across Functions

• Work effectively with developers designers product managers and data engineers.

• Communicate complex technical ideas clearly and lead teams towards shared goals.

Champion Best Practices and Safety

• Implement rigorous validation and evaluation frameworks.

• Establish guardrails for bias mitigation safety and privacy.

Innovate Continuously

• Stay abreast of the latest GenAI research and technologies.

• Proactively identify opportunities for impact and improvement.

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 Macs 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 and register with our referral code: MAC.

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.