AI Engineer

Nava Benefits

. Build and harden the platform underneath Nava’s LLM-based products .

Posted 9/15/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing LLM-based product infrastructure, with a focus on agent state management, orchestration, and zero-trust execution environments. Proficient in modern full-stack development using TypeScript and Python, with a strong emphasis on integrating foundation-model APIs and ensuring efficient resource management.

Highest-signal resume keywords

LLM-Based Product Infrastructure OwnershipAgent Runtime ManagementFull-Stack Development in TypeScript and PythonIntegration of Foundation-Model APIsExperience with Sandboxed Execution Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

TypeScriptPythonAgent State ManagementOrchestrationLLM Feature ShippingContext ManagementModel RoutingToken Usage OptimizationPostgresLangfuse

Soft Skills

Decision ExplanationProblem-Solving

Tools & Technologies

AWSReactNodeFoundation-Model APIs

Industry Keywords

Zero-Trust ExecutionSandboxed ExecutionEvaluation and TracingAI Use Cases

Tech Stack

Tools & technologies

AWSNode.jsPostgresPythonReactTypeScript

About the role

Key responsibilities & impact

Build and harden the platform underneath Nava’s LLM-based products
Make context management, agent state, sandboxed execution, and model routing reusable across AI use cases
Design state management and deployment patterns that allow long-running agent tasks to survive deploys, restarts, and retries
Enable agent tasks to be resumed, inspected, and replayed
Package context into zero-trust execution environments across platforms
Eject and retrieve new context as agents work
Route models to appropriate jobs and orchestrate subagents
Measure and optimize token usage and reduce cost per task as volume grows
Reduce unplanned platform work interrupting AI product teams
Document, test, trace, and evaluate shared platform patterns
Enable new engineers to adopt shared patterns quickly and catch regressions before users notice

Requirements

What you’ll need

Hands-on ownership of infrastructure under an LLM-based product that other engineers or users depended on
Experience with agent runtime, context or state management, orchestration, or evaluation and tracing
Experience shipping LLM features to production and managing model behavior, latency, cost, and tradeoffs
Modern full-stack development in TypeScript and/or Python
Experience integrating foundation-model APIs, tool calling, and human review into an application
Practical evaluation and tracing habits
Ability to explain decisions to product, design, and domain experts
Ability to turn product and domain problems into reusable capabilities
Experience with React, Node, TypeScript, Python, Postgres, and AWS as relevant to the stack
Experience with multiple foundation-model providers
Experience with sandboxed execution environments for agents
Langfuse for tracing and evaluation is used in the stack
No specific framework, model provider, or minimum audience size is required
Coding agents are encouraged but not required in the interview

Benefits

Comp & perks

Website LinkedIn All Job Openings 51 - 200 employees Founded 2019 🏥 Healthcare 💼 Consulting 📦 Logistics 🔥 Funding within the last year 💰 $30M Series C - Nava on 2025-10 Healthcare
Consulting
Logistics Nava Benefits is a modern employee benefits broker that pairs elite benefits advisors with an AI-powered SaaS platform (HQ) to simplify benefits administration, streamline renewals, and provide 24/7 support to employees and their families. The company helps HR teams save time, lower healthcare costs, centralize benefits documents, run audits and benchmarking, and offer AI-driven, self-serve member support and plan decision tools. Nava emphasizes alternative health plan strategies (self-funding, PBMs, captives) and positions itself as a tech-enabled extension of HR.