Sr. Software Engineer, Core AI

Navan • Palo Alto, CA

2d • $113,400 - $252,000

About The Position

Navan is building specialized AI services to improve high-value human workflows across the company. The Senior Software Engineer, Core AI will design, build, evaluate, and operate production-grade AI services and agents, owning work end to end—from data and context design through tool use, application logic, evaluation, and production monitoring. The role partners with AI Architecture, AI Ops, and Platform teams to ensure services are secure, reliable, cost-aware, and deployable at scale. It emphasizes iterative delivery, learning from real workflow outcomes, and measuring quality through repeatable evaluations and controlled experiments.

Requirements

• At least 5 years of strong software engineering experience delivering production services or products.
• Hands-on experience building AI/LLM-powered applications or agents used by real users or in operational settings.
• Experience evaluating AI behavior, including defining expected outcomes, building test sets or evaluations, tracking regressions, and acting on results.
• Ability to shape retrieval, context, and serialization so models receive the information needed for a task.
• Good judgment regarding tool use, autonomy, human review, failure handling, privacy, reliability, latency, and cost.
• A product-minded approach focused on solving specific workflow problems and measuring whether solutions work.

Nice To Haves

• Experience with agent runtimes, model APIs, MCP, tracing, or evaluation tools.

Responsibilities

• Design and implement task-specific AI services and agents, including data serialization, retrieval, memory where appropriate, tool integrations, and bounded multi-step reasoning.
• Work with partners to define expected behavior and create and maintain evaluations using representative examples.
• Use evaluation results, failure analysis, and production feedback to improve context and data, service logic, tools, and model behavior.
• Integrate tracing, observability, versioning, monitoring, reliability practices, and success metrics into owned services.
• Run controlled, repeatable experiments comparing models, data, and implementation approaches.
• Partner with AI Architecture, AI Ops, and Platform teams to make services secure, reliable, cost-aware, and scalable for deployment.
• Move from user problem to prototype to production iteratively, learning from real workflow outcomes.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed