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Build and operate customer-facing AI agent experiences for loyalty programs, including LLM workflows, tool calling, guardrails, evaluations, monitoring, personalization, and streaming chat. Integrate frontend, backend, APIs, data services, and AI orchestration layers. Partner cross-functionally to ship measurable products, maintain quality, protect sensitive data, and support features in production.
Navan is building the next generation of intelligent travel experiences, where loyalty, personalization, and AI agents help travelers make better decisions before, during, and after every trip. As a Senior Software Engineer, AI on the Loyalty Wallet team, you’ll build agentic product experiences that understand a traveler’s loyalty programs, surface useful insights, and safely help users manage their memberships through Navan Edge.
What You’ll Do:
- Build AI-Powered Product Experiences: Design and develop agentic workflows that help users view, understand, connect, and manage their loyalty programs through chat, wallet surfaces, and personalized recommendations.
- Develop Production AI Systems: Build reliable LLM-powered flows with structured outputs, tool calling, guardrails, human confirmation, evals, and monitoring for real customer-facing use cases.
- Own Agent and Workflow Quality: Create and maintain scenario tests, adversarial evals, prompt/tool contracts, and quality metrics that ensure agents behave safely around loyalty data, PII, financial guidance, and unsupported requests.
- Integrate Across the Stack: Work across frontend, backend, and AI orchestration layers, including wallet APIs, streaming chat experiences, UI components, data services, and ML/LLM workflows.
- Turn Data Into Personalization: Help transform loyalty balances, tier progress, membership data, connected email signals, and trip context into useful recommendations and next-best actions.
- Collaborate Cross-Functionally: Partner closely with product, design, backend, data, and platform teams to ship polished, measurable customer experiences.
- Raise the Engineering Bar: Champion maintainable code, thoughtful abstractions, strong tests, observability, documentation, and operational ownership.
What We’re Looking For:
- 6+ years of software engineering experience building production systems, with meaningful hands-on experience in AI, LLM, agent, workflow, or ML-powered products.
- Experience building agentic systems, tool-calling workflows, RAG-like systems, structured LLM outputs, eval pipelines, or AI assistants in production.
- Strong engineering fundamentals in TypeScript/Node.js, Java, Python, or similar backend/product engineering stacks.
- Experience with distributed systems, APIs, async workflows, caching, observability, and production debugging.
- Comfort working with AI safety patterns such as guardrails, HITL confirmation, deterministic tool boundaries, hallucination prevention, and PII-sensitive workflows.
- Product mindset and ability to translate ambiguous user needs into robust, user-facing experiences.
- Strong ownership mentality, with the ability to ship, measure, iterate, and support features after release.
- Experience with travel, loyalty programs, personalization, fintech, or consumer data products is a strong plus.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent hands-on experience.
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.
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.
Navan Palo Alto, California, USA Office
3045 Park Blvd, Palo Alto, CA, United States, 94304
Navan San Francisco, California, USA Office
181 Fremont St. 23rd Floor , San Francisco, CA, United States, 94105
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