Sr. Software Engineer, Core AI

Navan
Palo Alto +1 more
On-site

In the 12 months to 30 Jun 2026, Navan filed 6 H-1B positions titled "Senior Software Engineer". Source: U.S. Department of Labor, LCA disclosure data. A record of filings already made, not a commitment to sponsor.

Who this role is best for

Geared toward candidates comfortable with building AI services and end-to-end system ownership, with a focus on production-grade implementation and collaboration across engineering and AI teams in the Bay Area.

Best fit for

  • Candidates with 5+ years of experience in building AI/LLM-powered applications for operational use
    — “5+ years of strong software engineering experience delivering production services or products, ideally at senior or staff level.”
  • Individuals who can design and implement AI services with a focus on data and context
    — “design and implement task-specific services and agents, including data serialization, retrieval, memory where appropriate, tool integrations, and bounded multi-step reasoning.”
  • Candidates who thrive in a collaborative environment across AI Architecture, AI Ops, and Platform teams
    — “work with AI Architecture, AI Ops, and Platform teams to make services secure, reliable, cost-aware, and deployable at scale.”

Things to consider

  • The role requires a strong focus on production systems and monitoring for AI services
    — “Build for production: integrate tracing, observability, versioning, monitoring, reliability practices, and success metrics into the services you own.”
  • This position may require working with AI-assisted tools during the application review process
    — “Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role.”

How to stand out

  • Highlight experience with AI evaluation methods and measurable improvements in model performance
    — “Experience with evaluation methods for AI behavior: defining expected outcomes, building test sets or evals, tracking regressions, and acting on results.”
  • Showcase a data-first mindset with examples of shaping retrieval and context for AI tasks
    — “A data-first mindset: able to shape retrieval, context, and serialization to give a model the information needed for the task.”
  • Emphasize your ability to ship iteratively and learn from real workflow outcomes
    — “Ship iteratively: move quickly from user problem to prototype to production, learning from real workflow outcomes.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • successful AI service launches
  • improved AI service quality
Typical background
5+ years of software engineering experience

Skills & requirements

Required

AI ServicesProduction MonitoringEvaluation MethodsData-first MindsetTool UseProduct-minded Approach

Preferred

Agent RuntimesModel ApisTracingEvaluation Tools

Stack & domain

AILLMEvaluation MethodsData SerializationRetrievalMemoryTool IntegrationsMulti-step ReasoningTracingObservabilityVersioningMonitoringReliabilitySuccess MetricsAgent RuntimesModel ApisMCPEvaluation ToolsProblem SolvingDecision MakingTeamworkLeadership

About the role

Original posting from Navan

About the Role

We are building a fleet of specialized AI services that improve high-value human workflows across the company. As a Senior Software Engineer, Core AI, you will design, build, evaluate, and operate production-grade AI services and agents. You will own work end to end—from data and context design through tool use, application logic, evaluation, and production monitoring.

What You’ll Do:

Build specialized AI services: design and implement task-specific services and agents, including data serialization, retrieval, memory where appropriate, tool integrations, and bounded multi-step reasoning.

Define and evaluate quality: work with partners to make expected behavior explicit, write and maintain evals against representative examples, and use results to measure performance against expectations.

Improve quality systematically: use evaluation findings, failure analysis, and production feedback to improve context and data, service logic, tools, and model behavior.

Build for production: integrate tracing, observability, versioning, monitoring, reliability practices, and success metrics into the services you own.

Run controlled experiments: compare models, data, and implementation approaches using repeatable benchmarks so improvements are attributable and reproducible.

Partner on architecture: work with AI Architecture, AI Ops, and Platform teams to make services secure, reliable, cost-aware, and deployable at scale.

Ship iteratively: move quickly from user problem to prototype to production, learning from real workflow outcomes.

What We’re Looking For:

5+ years of strong software engineering experience delivering production services or products, ideally at senior or staff level.

Hands-on experience building AI/LLM-powered applications or agents with real users or operational use.

Experience with evaluation methods for AI behavior: defining expected outcomes, building test sets or evals, tracking regressions, and acting on results.

A data-first mindset: able to shape retrieval, context, and serialization to give a model the information needed for the task.

Good judgment about 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 the solution works.

Comfort learning tools and frameworks; experience with agent runtimes, model APIs, MCP, tracing, or evaluation tools is helpful.

The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity.

For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.

Pay Range$113,400—$252,000 USD 

Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers. 

Human oversight: Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application. 

Your rights: If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email here. Your decision to do so will not affect how your candidacy is evaluated. 

Please refer to our Candidate Privacy Notice for more information about our processing of personal data, and your rights.

Source: Navan careers

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