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.
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.
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