Lead GenAI Agent Developer

Fannie Mae Corp•Reston, VA

32d•$138,000 - $180,000•Hybrid

About The Position

As a Lead GenAI Agent Developer , you will serve as a subject matter expert to drive the engineering needs of the LLM platform, including the GenAI Gateway (Portkey), AWS AI services (AWS Bedrock and foundational models), observability, and customer support for internal and external applications. You will lead full stack development efforts across AI platform components, integrating cloud-native services, enhancing monitoring and telemetry, and supporting application teams consuming LLM capabilities. The ideal candidate will bring deep expertise in both front-end and back-end engineering, cloud infrastructure, and AI service integration, with a strong focus on building resilient, scalable, and secure systems. The Lead GenAI Agent Developer role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

Requirements

Proven experience in platform engineering, cloud architecture (preferably AWS), and AI/ML service integration.
Strong understanding of Large Language Models, observability tools and practices.
Experience leading hybrid teams (FTEs and contractors).
Excellent communication and stakeholder management skills.
Passion for building scalable, secure, and customer-centric AI platforms.
Angular
Java Frameworks
JavaScript
Python Frameworks

Nice To Haves

Bachelor degree or equivalent

Responsibilities

Lead engineering efforts for the GenAI Gateway platform, focusing on scalability, reliability, and integration with enterprise AI services.
Architect and optimize solutions using AWS services, including Bedrock and other foundational models.
Enhance observability across platform components to ensure proactive monitoring, issue resolution, and performance tuning.
Provide technical leadership and support for the Fannie Mae application, ensuring seamless integration and high-quality customer experience.
Collaborate with cross-functional teams to align platform capabilities with business needs and AI adoption strategies.
Build secure integrations (via APIs, MCP, and connectors) with internal data sources (e.g. SharePoint, Confluence, Jira, ServiceNow).
Manage versioning, testing, and deployment pipelines for custom GPTs, MCPs, Agents and plug-ins.
Optimize performance and reliability - monitoring usage, latency, and API costs.
Mentor and guide engineering teams, fostering a culture of innovation, accountability, and continuous improvement.

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