AI Software Developer, Senior

Booz Allen Hamilton•San Diego, CA

1d•$86,900 - $198,000

About The Position

This role is for an AI Software Developer, Senior in the San Diego region, focusing on cybersecurity and mission challenges for Navy efforts. The position involves working within a skilled team that collaborates deeply with clients and mission stakeholders to clarify problems, shape technical approaches, and deliver practical outcomes in secure, compliant settings. It is a multidisciplinary environment where individuals may engage in advisory conversations, solution and implementation planning, and focused integration and implementation, including AI-enabled automation and analytics to reduce risk and improve the speed and quality of cyber and mission workflows. The role requires working with cybersecurity specialists, engineers, and partners supporting Navy customers and warfare centers. Success depends on curiosity, ownership, and comfort working in classified or controlled environments. Strong communication, sound judgment, and the ability to translate between mission language and technical reality, with a constant focus on security, RMF, and operational constraints, are valued. The team delivers outcomes that reduce cyber risk and support the fleet and ashore enterprise, modernizing Navy cyber missions through the responsible use of data, automation, and AI.

Requirements

4+ years of experience in a role that includes software development, integration, or automation in a professional environment
Experience in Python for developing, testing, and debugging components others rely on services, automation, and data or integration utilities
Experience integrating APIs and working with relational, document, or NoSQL stores, and tracing failures across components
Experience delivering in small teams with Agile, Kanban, or structured collaboration, and with Git and code review norms
Experience with cloud or enterprise deployment patterns or on-prem integration environments
Ability to translate mission or security requirements into concrete technical tasks and explain tradeoffs to stakeholders
Secret clearance
Bachelor’s degree in Computer Science, Computer Engineering, Cybersecurity, Information Systems, or a STEM field
DoD 8570/8140 IAT Level II certification

Nice To Haves

Experience designing AI/ML or LLM-enabled architectures, including model selection, workflow design, orchestration, and integration into mission workflows
Experience with AI/ML or LLM-enabled patterns, including RAG, embeddings, vector search, prompt or tool orchestration, or frameworks such as OpenAI Agents SDK, Google ADK, LangChain, or comparable
Experience with enterprise data and analytics platforms the team may leverage including DoD's Advana or War Data Platform (WDP), Databricks, and Palantir Foundry
Experience implementing AI/ML or LLM solutions and model deployment locally or through cloud-based technologies
Experience conducting process transformation analyses, mapping as-is and to-be workflows, and developing solution blueprints
Experience with LLM model registries, such as Hugging Face, embedding models, and vector databases
Experience with cloud-based technologies, such as AWS, Azure, or GCP, and software version control and containerization
Knowledge of networking, security, and system architecture
TS/SCI clearance
Master's degree in Computer Science, Computer Engineering, Information Systems ora related technology field

Responsibilities

Understand the client and the problem: participate in discussions with mission and technical partners to clarify objectives, constraints, and security or compliance boundaries.
Shape solutions: contribute to technical approaches, tradeoff analysis, and implementation plans such as what to build or integrate, how to phase work, and what evidence or controls matter.
Deliver hands-on technical work: design, implement, test, and troubleshoot scripts, services, APIs, or automation, including AI/LLM-assisted workflows where appropriate, so recommendations are credible and deployable, not slide-only.
Integrate systems and data: work with REST/HTTP APIs, data stores, and enterprise or cloud patterns to connect capabilities safely and repeatably.
Document and communicate: produce clear artifacts for technical and non-technical audiences such as design notes, limitations, operational implications, or security-relevant behaviors.
Respect the cyber context: align work with RMF, control expectations, and secure engineering practices, and partner with cybersecurity and authorization stakeholders.
Improve how we work: use version control, review practices, and lightweight testing appropriate to the engagement, and stay current on responsible AI expectations in government settings.