AI/ML Software Engineer

Booz Allen Hamilton•Dallas, DC

18h

About The Position

AI/ML Software Engineer The Opportunity : To achieve an organization’s mission, leaders need strong team members who can create and analyze processes, communicate requirements, and develop innovative solutions throughout the execution of the mission. Whether reviewing program-wide technical architecture or providing AI / ML expertise, our clients need someone who combines deep technical understanding of sof t war e engineering with strong architectural judgment. That is why we need you, an experience d AI / ML Sof t war e Engineer who can operate at a system-of-systems level to support clients in advancing AI-enabled systems within an R & D environment. As part of our team, you'll serve as a strategic technical advisor to the Advanced Research Projects Agency for Health ( ARPA-H ) , helping conceptualize, create, and execute advanced government-funded R&D programs to accelerate better health outcomes for everyone. You’ll work with world-class scientists and engineers to support the development of high-impact solutions to society's most challenging health problems. You’ll leverage technical expertise to provide strategic assessments of new technologies in support to senior ARPA-H decision makers. You’ll maintain responsibility for producing and presenting findings and recommendations to a team of colleagues and clients on the feasibility and potential impact of future research programs, assisting with the management of current programs, and facilitating commer cia lization of successfully developed technologies. You'll serve as an AI / ML Sof t war e Engineer advising program leadership and supporting sof t war e engineering to support the client mission. You will support clients in ensuring that program-wide technical architecture and engineering to rigorous AI development, evaluation, and long-term impact. Your attention to detail, flexibility, communication skills, understanding of the client's mission, and problem-solving will enable the mission's success.

Requirements

5+ years of experience delivering production-ready, industrial strength code, and implementing CI / CD pipelines
Experience in Python and with libraries such as TensorFlow and PyTorch
Experience with neural network architecture, including transformers, and NLP techniques
Experience with LLM tool or function calling and agentic orchestration
Experience handling and preprocessing large datasets, and with data pipelining and ETL processes
Experience with cloud platforms such as AWS, Google Cloud, or Azure, for deploying ML models
Experience with sof t war e engineering fundamentals, including version control, testing, and CI / CD
Ability to design efficient algorithms for data retrieval and model training, and optimize models through hyperpara met er tuning
Ability to travel up to 25% of the time
Master’s degree

Nice To Haves

Experience producing and presenting high-quality technical documentation and presentations in a fast-paced, dynamic environment
Experience operating in an R & D environment

Responsibilities

Deploy AI models and services on cloud platforms such as AWS, Google Cloud, or Azure.
Collaborate with cross-functional teams, including data scientists, researchers, and other engineers, to integrate LLMs and RAG into broader projects.
Extend agentic capabilities, including agent orchestration and tools calling, using MCP and A2A.
Communicate technical concepts and project progress to non-technical stakeholders and team members.
C ond uct experiments to fine-tune para met ers and optimize model performance.
Implement techniques to improve the efficiency and scalability of LLM and RAG systems.
Stay up-to-date on the most current developments in the generative-AI space.
Monitor and maintain deployed models to ensure they perform reliably and meet performance benchmarks.
Ensure code quality by following best practices in sof t war e development, including version control, testing, and continuous integration or continuous deployment ( CI / CD ) .
Document code and maintain comprehensive technical documentation to support team knowledge sharing and project handovers.