Forward Deployed AI Engineer (Senior)

AZX; Seattle (WA); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive compensation

Healthcare with coverage

Flexible time off

Stock equity

401k

Fully remote with Seattle cluster

Immersive in-person summits

Job summary

AZX is hiring a Forward Deployed Engineer to scope, build, deploy, and measure AI systems inside client environments across utilities, real estate, and logistics. You’ll bring the right mix of models and tools, work with client operators, and verify outcomes with auditable numbers.

You will collaborate with our team across DevOps, data pipelines, frontend, and backend to deliver end-to-end solutions while maintaining a strong engineering presence with client IT and security stakeholders.

Qualifications

• 5+ years of full-stack delivery experience.
• Experience shipping LLM/agentic systems to production with structured outputs.
• Ability to deploy inside someone else’s cloud, identity, and compliance constraints.
• Strong stakeholder and executive communication and discovery skills.

Responsibilities

• Own client delivery end-to-end from discovery to handover.
• Build eval harnesses, replay loops, guardrails, and cost/latency budgets.
• Design and ship high-stakes systems with measurable baselines and success metrics.
• Collaborate with DevOps, data, frontend, and backend teams across client engagements.
• Maintain client-facing engineering presence with IT/security teams and demos.

Skills

Full-stack delivery

Python/FastAPI backends

React/TypeScript front ends

LLM/agentic systems

Deployment in client/cloud envs

Stakeholder management

Tools

PostgreSQL

Redis

LangGraph

CrewAI

Job description

Our mission is to accelerate positive impact in critical industries through AI transformation .

We’re a public benefit corporation , founded in 2024. We bootstrapped profitably for our first year and are now backed by leading investors focused on AI, climate and energy.

We’re growing quickly and already work with category-leaders in real estate (CBRE), energy (Franklin Energy), logistics (Flexe) and power utilities such as Puget Sound Energy and others.

We're built on three simple ideas:

• We're at the intersection of two massive transformations: AI and climate change.
• AItechnology is far outpacing critical industry's ability to harness it.
• The most impactful opportunities are often in messy business processes.

To tackle this, we've put together a different kind of company.We're not a SaaS company, nor a typical consultancy.

Instead we're focused on client problems and impact. We create solutions that combine consulting, custom engineering and reusable approaches (data, code, models...).

AZX is led by experienced founders from AI and climate focused companies.

Working at AZX

We hope AZXis the best career step you ever take. We're aiming to build the kind of company we dreamed of:positive impact, fun, interesting problems, enjoyable colleagues (high EQ, low drama), flexible work-life and built to last.

While we're an early-stage startup, we do offer:

• Competitive compensation for our stage of company, including base and bonus
• Healthcare with meaningful coverage for dependents and HSA
• Flexible time off
• Stock equity
• 401k
• Fully remote culture with a cluster of colleagues in Seattle
• Twice-yearly immersive in-person summits as well as training opportunities

As we grow, we'll continue to add new benefits (though if you're driven by perks, you might be happier at big tech).

It's just the beginning for AZX.

Location

United States

Employment Type

Full time

Location Type

Remote

Compensation

We offer competitive early-stage startup compensation based on your capabilities, experience, and location

About AZX

Our mission is to accelerate positive impact in critical industries through AI transformation.

We’re growing quickly and already work with category-leaders in real estate (CBRE), energy (LevelTen Energy), logistics (Flexe) and utilities.

We’re a public benefit corporation, founded in 2024 and have been profitable from inception.

We work on challenges in clean energy, decarbonization, climate risk, energy systems and global economics. We’re building our company for long term success and aim to build the ultimate place to work if you’re passionate about AI and positive impact.

About the Role

We are seeking a Forward Deployed Engineer to join a team that scopes, builds, deploys, and measures AI systems inside client environments — utilities, commercial real estate, and logistics. Your software runs in the client's cloud, under their identity provider and toolchain, inside their compliance framework, integrated with their systems of record — you bring the right mix of models and tools for the job rather than working around it. The work is agentic AI with a correctness envelope: think document intelligence with deterministic, auditable validation where money or compliance is on the line, voice-of-customer AI, cognitive digital twins of a client's customers, and human-in-the-loop agentic workflows, all measured against real before/after baselines rather than left as shelf-ware. You won't be handed a finished spec — you'll sit with the client's operators and executives to find the real problem, design the solution with their architects, build it with your pod, and prove it worked with numbers both companies stand behind. You bring a strong area of expertise and expect to use it, and work closely with our team across DevOps, infrastructure, data pipelines, front end, and back end as the engagement requires — you are the engineering face of AZX.

Responsibilities:

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.

Extract structured facts from messy documents (like contractor bids or engineering forms) and build the deterministic checks that gate money- or compliance-sensitive answers, making "cannot determine" fail closed rather than open.

Optimize pipelines for cost and quality — for example, moving a step from a frontier model to a fine-tuned small model or a deterministic rule, then proving quality held with a replay harness.

Design and ship high-stakes systems like after-hours voicemail triage, defining the right autonomy boundary for the risk involved.

Agree on and track the measurement story with the client — KPIs, baselines, and instrumentation for cost, performance, and quality — in writing before deployment and validated after.

Maintain client-facing engineering presence: working sessions with their IT/security teams, demos, POCs that derisk the next engagement, and a feedback loop that carries field-learned requirements back to the platform team.

Core Qualifications:

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

Practical fluency across our stack Python (async/FastAPI/Pydantic), TypeScript/React, Postgres/pgvector, Redis, LLM provider APIs, RAG/hybrid retrieval, and agent frameworks (LangGraph/AutoGen/CrewAI-class or hand-rolled loops).

Familiarity with enterprise