Advisor Software Engineer; AI​/ML

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. As an Advisor Software Engineer (AI/ML), you will design, produce, test, or implement software, technology, or processes across multiple projects, programs, or products, and create and maintain IT architecture, large‑scale data stores, and cloud‑based systems.

Location:

Reston, VA. This role is an independent contributor at the manager level. Compensation: $155,000 – $209,000.

• Determine the needs of the customer groups across multiple projects, programs, or products while identifying and resolving conflicting or complementary needs across customer groups.
• Design and develop software solutions to meet needs and may also lead matrixed teams.
• Apply extensive expertise in process‑driven approach in designing solutions.
• Implement new software technology and coordinate simultaneous implementation tasks across teams.
• Oversee the maintenance of existing software.

• 6years of hands‑on software engineering experience designing, developing, and maintaining scalable enterprise applications and cloud‑native solutions.
• Strong proficiency in Python development, including backend services, APIs, automation, data processing workflows, and production‑ready AI/ML applications.
• Strong skills in system design and architecture, including scalable, resilient, secure, and maintainable solution design.
• Experience building API‑driven solutions, including REST APIs, microservices, service orchestration, secure API development, and enterprise system integrations.
• Hands‑on experience with AWS cloud‑native development, including serverless, event‑driven, containerized, and distributed application patterns.
• Experience with SQL and data platforms, including PostgreSQL, Snowflake, or similar relational and analytical database technologies.
• Deep understanding of the software development lifecycle, including requirements analysis, design, development, testing, deployment, production support, and maintenance.
• Experience with engineering best practices, including secure coding, code reviews, automated testing, CI/CD, observability, performance tuning, and production issue resolution.
• Experience collaborating with technical and business stakeholders, including translating business needs into technical solutions and communicating risks, trade‑offs, and delivery impacts.

• Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology, Data Science, Machine Learning, Artificial Intelligence, or a related field.
• Experience designing and delivering AI‑enabled enterprise software solutions, including GenAI applications, intelligent automation, AI‑assisted workflows, and AI‑driven decision support.
• Experience with MLOps, vector databases, embedding‑based search, MCP‑based tool integration, and enterprise AI governance practices.
• Experience writing technical papers, invention disclosures, patent‑supporting documentation, or reusable engineering playbooks for emerging technology solutions.
• Experience with testing strategies and tools, including unit, integration, functional, regression, and performance testing.
• Experience with Scaled Agile Framework, Agile methodology, cybersecurity vulnerability remediation, and enterprise delivery practices.
• Strong relationship management skills with the ability to collaborate across stakeholders, influence outcomes, and support strategic enterprise technology initiatives.

• Hands‑on AWS software engineering experience, including application development using AWS service APIs, AWS CLI, AWS SDKs, and cloud‑native deployment patterns.
• Hands‑on experience with core AWS services, including AWS Lambda, Amazon S3, Amazon EC2, Amazon API Gateway, IAM, Cloud Watch, Event Bridge, SQS, SNS, and Step Functions.
• Experience with AWS AI/ML services, including Amazon Sage Maker, Amazon Bedrock, and AWS‑based model deployment or inference patterns.
• Experience with containers and Dev Ops practices, including Docker, Kubernetes, ECS/EKS, CI/CD pipelines, automated testing, and release management.
• Understanding of cloud security…