Software Engineer, Professional (Gen AI Data Scientist)

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. Continue your career journey where your work contributes to a greater purpose.

Position Overview:

We are seeking an Software Engineer, Professional - Gen AI (Data) Scientist with a strong focus on Generative AI (Gen AI) to lead the design and development of cutting‑edge AI Agents, Agentic Workflows and Gen AI Applications that solve complex business problems. This role requires advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi‑modal AI, Gen AI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments. You will serve as a hands‑on Gen AI (data) scientist and critical thought leader, working alongside full stack developers, UX designers, product managers and data engineers to shape and implement enterprise‑grade Gen AI solutions.

Our Impact:

At Freddie Mac, we are at the forefront of technological innovation, developing AI solutions that transform complex business challenges into streamlined, automated processes. By leveraging cutting‑edge AI Agents, Agentic Workflows, and Gen AI Applications, we enable businesses to enhance their operational efficiency, make data‑driven decisions, and unlock new opportunities for growth. Our commitment to integrating advanced technologies like LLMs and multi‑modal AI into enterprise solutions ensures that we remain leaders in the AI industry, delivering impactful and sustainable results for our clients.

Your Impact:

As Software Engineer, Professional- Gen AI (Data) Scientist, your role is pivotal in shaping the future of AI‑driven business solutions. You will have the opportunity to design and develop scalable applications that integrate sophisticated AI models, directly influencing how businesses operate and succeed. Your expertise in Automated QA and Python‑based microservices will be crucial in creating robust quality‑controlled frameworks for Gen AI solutions that will help with Governance Approvals. By collaborating with Gen AI scientists, UX designers, and other cross‑functional teams, you will drive the implementation of enterprise‑grade Gen AI solutions, ensuring they meet the highest standards of performance and reliability.

Key Responsibilities:

• Design and implement scalable AI Agents, Agentic Workflows and GenAI applications to address diverse and complex business use cases.
• Evaluate and adapt models such as Claude (Anthropic), Azure OpenAI, and open‑source alternatives for business use cases.
• Train, Fine‑tune, optimise and Test lightweight Large Language Models (LLMs) to address diverse and complex business use cases.
• 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 Bedrock's 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).
• 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 anonymise data from PDFs, video, and audio sources for use in LLM‑powered workflows—leveraging 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 drives—map media content to vector representations using embedding models, and integrate with vector stores (AWS Knowledge Base/Elastic/Mongo Atlas) to support RAG architectures.

Qualifications:

• Bachelor's in data science/computer science with Machine Learning focus, Business Analytics. Advanced studies/degree preferred.
• 2-4 years of experience in Data Science, Computer Science with focus on Machine Learning and Business Analytics.
• At least 2 years in applied Gen AI or LLM‑based solutions preferred.
• Experience training and testing Machine/Deep Learning, Natural Language Models.
• Proven experience with AI development on AWS SageMaker, Bedrock, ML Flow on EKS.
• Strong programming skills in Python and ML libraries (Transformers, Lang Chain, etc.).
• Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks.
• Demonstrated ability to work in cross‑functional agile teams.
• Deep expertise in prompt engineering, fine‑tuning, RAG, Graph RAG, vector databases (e.g., AWS Knowledge Base / Elastic), and multi‑modal models.
• Published contributions or patents in AI/ML/LLM domains.
• Hands‑on experience with enterprise AI governance and ethical deployment frameworks.
• Familiarity with CI/CD practices for ML Ops and scalable inference APIs.

Keys to Success in this Role:

• Deep Gen AI Expertise: Master generative AI technologies, including LLMs and multi‑modal AI, to design innovative solutions.
• Prompt Engineering Proficiency: Excels in crafting effective prompts for optimizing AI model interactions.
• Analytical Problem‑Solving: Apply strong analytical skills to adapt AI models for complex business challenges.
• Collaborative Teamwork: Communicate effectively with cross‑functional teams to integrate AI solutions seamlessly.
• AWS Cloud Deployment Skills: Utilize AWS platforms like SageMaker for scalable AI application deployment.
• AI Governance and Ethics: Implement robust validation procedures to ensure ethical and compliant AI solutions.
• Continuous Learning: Stay adaptable and keep up with the latest AI advancements.
• Scalable Solution Development: Focus on creating scalable AI agents and workflows for diverse use cases.
• API Integration: Develop skills in API‑based integration for seamless deployment within enterprise systems.
• Data Management Expertise: Curate and manage enterprise data for robust AI development.

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.

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 $103,000 - $155,000 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.