Senior AI Operations (AI Ops) Engineer
Navan INC - Palo Alto, CA
Posted Feb 10, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- $116K-$258K From the posting source checked Jun 20, 2026
- 401(k) match
- Not verified
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Market context
- U.S. role benchmark (BLS OEWS)
- $116,543 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +9.8% - Much faster than average
60% above the BLS role benchmark for software engineering aggregate.
Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Senior AI Operations (AI Ops) Engineer Palo Alto, CA At Navan, we aren't building a single, generic chatbot. We are building a Composable AI Microservice Architecture , a swarm of hundreds of hyper-specialized AI services, each meticulously "programmed" to solve small, focused tasks with high precision. This fleet powers Ava , our AI support engine, and a suite of cutting-edge generative tools for travel and expense management. As a Senior AI Operations (AI Ops) Engineer , you are the architect of the platform that makes this scale possible. You will move beyond traditional MLOps to manage a "factory" of Language Models. Your challenge is one of orchestration and standardization, ensuring that every service in the swarm meets a rigorous bar for quality, reliability, and cost-efficiency. What You'll Do Orchestrate the AI Fleet: Build and own the runtime environment for 100+ specialized AI services. Manage model routing, context versioning, and standardized memory/history stores. High-Density Inference Optimization: Design and implement SageMaker Multi-Model Endpoints (MME) and Inference Components to serve multiple tuned SLMs per GPU, maximizing hardware utilization while minimizing latency. Deterministic Service Excellence: Treat reliability as a layered engineering problem. Build deterministic "shells" around probabilistic LM outputs, prioritizing data-layer validation and strict serialization. Automated Evaluation & Observability: Implement "LLM-as-a-judge" patterns and automated benchmarking to detect semantic drift and hallucinations across the fleet before they impact the user. Standardize the Workflow: Obsess over building reusable patterns and Terraform-based infrastructure that eliminate "snowflake" configurations, allowing us to deploy new specialized AI tasks in minutes.
Read the full description at navan.com. FewerJobs shows a preview and links to the original posting.
Apply link verified; last checked Aug 3, 2026.
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