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.
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.
Skills Required
- 6+ years of software engineering experience building production systems
- 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, or AI assistants in production
- Strong engineering fundamentals in TypeScript/Node.js, Java, Python, or similar backend/product stacks
- Experience with distributed systems, APIs, async workflows, caching, observability, and production debugging
- Comfort with AI safety patterns: guardrails, HITL confirmation, deterministic tool boundaries, hallucination prevention, PII-sensitive workflows
- Product mindset and ability to translate ambiguous user needs into robust user-facing experiences
- Strong ownership mentality; ability to ship, measure, iterate, and support features after release
- Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent hands-on experience
- Experience with travel, loyalty programs, personalization, fintech, or consumer data products
What the Team is Saying
Navan Compensation & Benefits Highlights
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Fair & Transparent Compensation — Pay aligns with mid‑ to upper‑market in core engineering and GTM roles, with competitive cash, equity, and bonus plans. Defined pay bands and commission tiers provide clarity on how earnings are structured.
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Leave & Time Off Breadth — Flexible/unlimited PTO is part of the package alongside paid parental leave durations for birthing and non‑birthing parents. Time‑off policies are positioned as broad and supportive across the company.
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Wellbeing & Lifestyle Benefits — Travel‑centric perks (IATAN access and discounted personal travel) combine with connectivity/home‑office stipends, commuter benefits, in‑office meals/snacks, and pet insurance. Access to Headspace supports mental‑health resources.
Navan Insights
What We Do
Navan (Nasdaq: NAVN) is the leading all-in-one business travel, payments, and expense management platform that makes travel easy for frequent travelers. From finding flights and hotels to automating expense reconciliation, with 24/7 support along the way, Navan delivers an intuitive experience travelers love and finance teams rely on. See how Navan customers benefit and learn more at navan.com.
Why Work With Us
At Navan, we’re never satisfied with the status quo, and we know breakthrough ideas come from diverse perspectives. We are committed to cultivating a workplace that reflects the diversity of the customers we serve while fostering leadership and innovation.
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Navan Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
In-person connections is the foundation of Navan, the connections forged through face-to-face interactions improve company culture and what we can achieve together. We operate on a hybrid working model, which we define as four days a week in-office.
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