Senior AI Developer / Technical Lead

Job Family:

Data Science Consulting

Travel Required:

None

Clearance Required:

Ability to Obtain Public Trust

What You Will Do:

The Senior AI Developer / Technical Lead will lead the design, development, deployment, and delivery of complex artificial intelligence, machine learning, generative AI, and public health analytics solutions for the Centers for Disease Control and Prevention and related clients. This role combines hands-on technical leadership with end-to-end project oversight, translating program objectives into scalable AI architectures and actionable delivery plans. The position is responsible for guiding multidisciplinary teams, establishing secure and responsible AI development practices, managing technical risks, and ensuring high-quality, compliant solutions. The successful candidate will serve as a primary liaison between clients, product stakeholders, and technical teams while driving innovation, reproducibility, maintainability, and continuous improvement across AI and analytics workflows.

Key Responsibilities:

· Lead end-to-end planning, architecture, development, testing, deployment, and delivery of complex AI, machine learning, generative AI, and public health analytics solutions, ensuring scope, schedule, budget, security, performance, and quality objectives are met.

· Translate client, user, and program objectives into technical requirements, AI solution architectures, product roadmaps, work plans, milestones, and deliverables aligned with federal standards, responsible AI principles, and stakeholder expectations.

· Provide hands-on technical leadership to multidisciplinary teams of AI developers, machine learning engineers, data engineers, data scientists, biostatisticians, and epidemiologists, fostering collaboration, accountability, code quality, and high performance.

· Serve as the primary technical point of contact for clients and stakeholders, communicating AI capabilities, limitations, tradeoffs, delivery status, and risks while facilitating timely technical and product decisions.

· Design and develop production-ready AI solutions, including machine learning models, generative AI applications, retrieval-augmented generation workflows, intelligent agents, APIs, and reusable software components using modern development frameworks and cloud services.

· Establish and oversee software engineering and MLOps practices, including version control, peer review, automated testing, CI/CD, model evaluation, monitoring, performance optimization, documentation, and secure deployment across development, test, and production environments.

· Evaluate emerging AI technologies and select appropriate models, frameworks, platforms, and integration patterns based on solution requirements, cost, scalability, security, explainability, and operational sustainability.