Senior Software Engineer (Generative AI)

Freddie Mac•McLean, VA

14d

About The Position

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: We are seeking a highly experienced hands-on Agile Development Senior Software Engineer (Gen AI) to lead the design and development of cutting-edge Generative AI (Gen AI) Agents, Agentic Workflows, and Gen AI Applications that solve complex business problems. This role requires advanced proficiency in Python-based microservices for the orchestration layer deployed to AWS EKS (Kubernetes). You will serve as a hands-on engineer, working alongside Gen AI scientists, product managers, and data engineers to shape and implement enterprise-grade Gen AI solutions. A strong focus on DevOps and automated testing using Gen AI is essential for success in this role.

Requirements

Bachelor's degree in computer science, Computer Engineering, IT or a related field.
5-7 years of experience in software development and Automated QA, with 1+ years of experience with Gen AI based solutions.
Deep Expertise with Cucumber/Behave, Playwright and DevOps methodologies.
Deep expertise in Python and microservices architecture.
Proven experience with cloud-native development, particularly AWS services.
Strong programming skills and familiarity with AI/ML libraries and frameworks.
Demonstrated ability to work in cross-functional agile teams.
Experience with CI/CD practices and DevOps methodologies

Nice To Haves

Advanced studies/degree preferred.

Responsibilities

Develop and implement automated testing frameworks using Gen AI to enhance the reliability and performance of Gen AI Agents, applications and workflows.
Design and implement scalable Full Stack Gen AI Agents, Agentic Workflows, and applications to address diverse and complex business use cases.
Design and deploy Python-based microservices for robust orchestration and integration with Gen AI Large Language Models (LLMs).
Collaborate with Gen AI scientists to integrate machine learning models such as LLMs, RAG, and multi-modal AI into the application architecture.
Implement solutions leveraging modern design patterns and best practices for full stack development.
Build and maintain RESTful APIs to enable seamless communication between different system components.
Collaborate with cross-functional teams of full stack engineers, data engineers and Gen AI scientists to build full-stack Gen AI experiences.
Integrate Gen AI solutions with enterprise platforms via API-based methods and standardized patterns.
Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production-ready deployment.
Lead DevOps initiatives, including CI/CD pipelines, to ensure scalable and efficient deployment of Gen AI applications.