# Forward Deployed AI Engineer (Senior) at Azx

- Company: Azx
- What the company does: Tech transformation, societal shifts, and environmental disruption put enormous pressure on critical industries like energy, infrastructure, real estate, and others to adapt, pursue new growth opportunities, and optimize operations. Backed by Powerhouse Ventures.
- Company website: https://azx.io
- Type: Startups (AI role)
- Level: Senior
- Location: United States
- Work setup: Remote
- Pay: $140K to $230K base salary per year (USD)
- Posted: 2026-09-11
- Apply by: 2026-10-26
- Apply: https://jobs.ashbyhq.com/careers.azx.io/b4e7d679-e263-4e92-b6f1-fbb299755947
- Page: https://www.1752.vc/careers/jobs/azx-forward-deployed-ai-engineer-senior/

## About the role

Own your client's technical delivery end to end — discovery support, solution design, build, deployment into the client's environment, and a handover their team can actually run. Build the trust machinery behind every system you ship: eval harnesses, replay loops, guardrails, cost/latency budgets, monitoring, and a defined "what happens when it's unsure" path.

## What they're looking for

- 5 + years of full-stack delivery skills: Python/FastAPI backends, React/TypeScript front ends, deployment, monitoring, real test coverage, and careful data handling since your pod is the whole team
- Experience shipping LLM/agentic systems to production users, not prototypes, with structured outputs, tool use, retrieval, guardrails, and an eval loop you can defend to a skeptic
- A well-stocked technical toolkit and the judgment to use it: small task models (OCR, ASR, classification, reranking), classical NLP, fine-tuning/distillation, deterministic rules, caching, and a frontier model only where it earns its cost
- Experience deploying inside someone else's cloud, identity provider, repos, and compliance regime, and negotiating their IT constraints without losing the design
- Strong stakeholder skills, running discovery with front-line operators, delivering executive readouts, and pushing back plainly (with a cheaper or safer alternative already sketched) when the ask is wrong
- Comfort with ownership under ambiguity given a vague problem and a deadline, you return with a working thing or a good question

Tags: Engineering