Software Engineer (Client Solutions)
Summary
Builds AI-driven workflows (RAG, agent pipelines) for clients in climate/energy/logistics, bridging technical delivery with client collaboration. Focuses on shipping solutions fast while ensuring reliability, with occasional frontend work.
Software Engineer (Client Solutions)
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 (can’t say which large utility yet).
We’re a public benefit corporation, founded in 2024 and have been profitable from the beginning (bootstrapped with consulting).
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're looking for a Software Engineer to work with our clients, turning their hardest problems into deployed AI solutions. This role sits at the intersection of engineering and client partnership. You'll build the agentic workflows, document processing pipelines, and retrieval systems that make up the substance of client engagements — and often the lightweight interfaces clients use to interact with them. Some engagements are enterprise-style deployments where reliability matters most; others are fast-moving innovation sprints where speed to a working solution wins.
What you will do
You will work on software projects in client engagements, and over time, internal platform capabilities.
You will:
Turn ambiguous client problems into shipping code, moving fast from open-ended discovery to a working solution.
Build agentic workflows and applied AI pipelines — RAG, structured extraction, OCR/document AI, and agent orchestration — using tools like LangGraph, LlamaIndex, or comparable frameworks.
Stand up lightweight front-ends or app-builder-style interfaces when clients need a way to interact with what you've built, not just an API.
Build basic eval harnesses and golden datasets so you (and the client) know a pipeline is actually working before it ships.
Drive projects end-to-end, from discovery through deployment, collaborating closely with client and internal teams throughout.
Design and write code at the quality standard the moment calls for — sometimes “right,” sometimes “right now.”
Advocate for engineering best practices and a strong dev culture as one of our first engineers.
Core Qualifications - Technical and foundational
4+ years of experience building production LLM/agent pipelines — RAG, structured extraction, or agent orchestration — not just prototypes.
Comfort picking up whatever's needed for a client engagement, including light frontend work when a pipeline needs a face.
A practical sense for how to validate whether an AI system is actually solving the client's problem.
Strong client-facing communication and genuine comfort with ambiguity — you'll often be defining the problem as much as solving it.
Willingness to work on-site or in close collaboration with client stakeholders as engagements require.
Values and Culture Qualifications
High emotional intelligence and a learning mindset
Strong collaboration skills
Enjoy others' success and a fun, positive environment.
Comfortable making decisions in the face of ambiguity and course correcting as needed.
Bonus Qualifications (not required but a huge plus)
Experience in both startup and enterprise environments
Past work in energy, real estate, utilities, climate or related fields
Bonus if you have experience and passion in one or more of
Additional web frameworks (e.g. Svelte, Vue, Angular)
Lower-level languages e.g. C++, Rust
Networking paradigms e.g. GraphQL, Websockets
ML capabilities e.g. Sk-learn, xgboost, Pytorch/Tensorflow/JAX, Onnx…
Additional database types such as graph or vector databases
DevOps e.g. CI/CD pipelines, Docker, Kubernetes, Terraform, Pulumi and/or Bicep
Generative AI e.g. prompt engineering, RAG, fine-tuning, tooling ecosystem
Compensation & benefits
Competitive early-stage startup compensation (based on capabilities, experience, and location)
Bonus eligibility
Health insurance with meaningful coverage for dependents
Flexible paid time off
Equity
Fully remote culture with a cluster of teammates in Seattle
Training and learning opportunities
Be part of a fast-growing, profitable, mission-driven company with industry leading clients tackling the massive opportunity of AI transformation in critical industries
Logistics
Remote but only USA/Canada
Must be willing to travel to Seattle area for final interview and travel 2x/year for company summits
Applicants must be currently authorized to work in the United States on a full-time basis.
We are unable to sponsor or take over sponsorship of employment visas at this time.
Next steps
If this job sounds great, we’d love to hear from you. If you feel aligned to the company but don’t check all these boxes, we’d still love to hear from you!
As published by ashby
Name, Email, Resume
- Primary Phone Number optional
- Are you currently located in North America? yes / no
- Do you currently, or will you in future, require visa sponsorship to work in the US? yes / no
- Do you have at least 7+ years of professional software engineering experience yes / no
- Have you led the technical design and implementation of a significant feature or system from conception to deployment? yes / no
- Do you have experience directly mentoring junior engineers on technical design or coding best practices? yes / no
- Are you comfortable working on projects where the initial requirements or solutions are highly ambiguous, requiring you to help define them? yes / no
- Describe a time you significantly improved the reliability, performance, or maintainability of an existing system. (1-2 sentences) written answer
- In your last role, how often did you interact directly with non-technical stakeholders (e.g., product managers, clients) to gather requirements or explain technical concepts? choose one
- In a high-throughput FastAPI application using PostgreSQL, you need to implement a feature that involves writing data to the database, but also performing a relatively slow, external API call (e.g., to a third-party service for enrichment or notification) that doesn't need to block the primary database write operation. Describe your approach to integrating this external API call. Specifically, discuss the technical patterns you would use within the FastAPI application and any considerations for ensuring data consistency or handling failures in the external call. written answer
- At AZX, we're building systems that matter in critical industries like energy, real estate, and infrastructure, often navigating ambiguous problems. Beyond the technical challenge, what aspects of solving these kinds of real-world, high-impact problems truly excite or motivate you? Feel free to share a brief anecdote or personal reflection. written answer
- Did anyone refer you to AZX? If so, who? optional