Senior/Principal Software Engineer (AI)

Position summary

The Senior/Principal Software Engineer (AI) is a technical leader responsible for architecting, developing, and deploying scalable, production-grade AI solutions. They bridge the gap between advanced models and enterprise platforms, building Retrieval-Augmented Generation (RAG) pipelines, intelligent agents, and operational guardrails. They also establish architectural standards and mentor engineering teams. This client-facing position necessitates communicating complex AI system behaviors to both technical and business leadership. They routinely work with government stakeholders to get buy-in on technical initiatives. This role collaborates with the product team, government stakeholders, and other contractors to build new systems and make improvements to existing systems. These responsibilities support Nava’s culture and mission.

What you'll do

• Lead the end-to-end development of advanced AI solutions, including agentic systems, RAG pipelines, and multi-agent workflows.
• Design, build, and optimize LLM-powered autonomous agents, workflow orchestrations, and RAG frameworks.
• Create integrations to connect AI agents with enterprise data systems, APIs, and services. Focus on explainable AI and responsible AI principles.
• Develop and refine machine learning models and generative AI applications.
• Architect end-to-end AI infrastructure, define guardrails, access controls, responsible-AI checks, and compliance protocols to ensure ethical, secure model deployment, model versioning, deploy and manage AI agents on cloud platforms using CI/CD pipelines, and infrastructure as code.
• Implement monitoring, logging, and observability for agent interactions, monitor model drift, system latency, and token economics to maintain cost-per-use efficiency and system reliability.
• Develop metrics for evaluating and monitoring AI performance.
• Contribute to technical documentation, prototyping strategies, and recommendations for future scaling.
• Guide multi-disciplinary teams of software engineers, data engineers, and data scientists, setting the technical playbook and best practices.

Required Skills

• Proven experience designing and building production-grade systems using modern programming languages (e.g., Python, TypeScript, or similar).
• Strong background in product engineering — translating user and product requirements into reliable, maintainable, and well-tested software.
• Advanced proficiency in Python.
• Hands-on experience with multiple LLMs, developing or integrating generative AI applications, and building autonomous AI agents.
• Experience with AI/ML technologies, ML frameworks, and implementation of GenAI and Agentic AI frameworks.
• Experience with CI/CD pipelines, cloud computing platforms (AWS), containerization (Docker), and infrastructure as code (Terraform) for deploying AI applications.
• Strong understanding of API and system integration design, cloud architecture, and data workflows.
• Demonstrated ability to work iteratively—rapidly prototyping, testing, and improving features based on real-world feedback.
• Strong grounding in security, privacy, and accessibility principles, particularly when handling sensitive or regulated data.
• Excellent collaboration skills with cross-functional partners including design, product, and research.