Technical Analyst

Location: Hybrid (U.S.A). New Mexico preferred.

Position Type: Full-time

Reports to: Chief Technology Officer

About Apaluma

Apaluma Inc. is a startup dedicated to transforming dark data into actionable intelligence. We build AI-driven and physics-based technologies that help government agencies unlock insights from regulatory, environmental, and real-time monitoring data. Our mission is to provide transparent, data-backed decision-making tools that empower agencies to manage resources effectively and sustainably.

Our Team & How We Work

We are a small team. Engineering, data science, design, and product all work together directly. There is not a lot of ceremony, and people regularly move between areas as the work requires it. This role is a good fit if you like digging into the details, care about getting things right, and are energized by work that directly unblocks the people around you.

Communication matters a lot to us. With a team this size, things move quickly and context gets lost if people are not talking to each other. We try to be direct and kind at the same time, give honest feedback, and keep each other in the loop without overloading on meetings.

AI tools are a required part of how we work. Everyone on the team uses LLMs, copilots, and other AI-assisted tooling in their daily workflows. We are looking for someone who already works this way or is ready to start.

Role Overview

This is primarily a documentation and knowledge capture role.. The core of the job is reviewing permitting and regulatory workflows, understanding how they work at a technical level, and writing clear, detailed specs that engineering can build from without a lot of back-and-forth. A big part of why this matters right now: we are building agentic AI systems that automate portions of these workflows, and that requires someone who can document the processes thoroughly enough for both engineers and AI systems to act on them.

Right now, much of this work sits with our Chief Technology Officer and Head of Product. Adding a Technical Analyst means they can focus on higher-level product direction and architecture while you handle the detailed requirements, workflow documentation, and spec writing that keeps engineering moving.

This role does not require deep software engineering experience, but it does require a genuine interest in how technology works and the ability to bridge the gap between a regulatory process and a software requirement. Our platform deals with environmental permitting, compliance data, and monitoring systems, so the work is specific and substantive. There is a lot to learn, and we are open to someone earlier in their career who is sharp, thorough, and motivated to ramp up quickly.

For someone with a genuine interest in AI, ML, or agentic systems, this is a strong entry point. The work gives you direct exposure to how AI products get built from the ground up: how real-world processes get translated into structured data, how specs feed into AI-driven automation, and how a small team ships AI products for government clients.

Key Responsibilities

Requirements & Spec Writing

• Review environmental permitting workflows, regulatory requirements, and compliance processes to understand what the platform needs to support.
• Write detailed, structured specs that translate regulatory and business logic into clear requirements for engineering.
• Document workflows end to end: who is involved, what data moves where, what decisions get made, and what the edge cases are. This documentation feeds directly into our agentic AI development.
• Maintain and organize requirements documentation so it stays current and useful as the product evolves.

Unblocking Engineering

• Deliver specs with enough detail and clarity that engineers can start building without extended discovery conversations.
• Answer follow-up questions from engineering quickly and accurately. When you do not know the answer, figure it out.
• Identify gaps, ambiguities, or conflicts in requirements before they become engineering blockers.
• Work closely with the technical lead to make sure specs align with the platform architecture and data model.

Research & Domain Learning

• Learn the regulatory and permitting domain as it relates to our platform. This includes environmental permits (like Title V Air Permits, Discharge Permits etc), compliance reporting, and agency workflows.
• Research how government agencies handle specific processes and translate that understanding into product context.
• Stay current on the data sources, standards, and terminology relevant to the work.

Collaboration & Communication

• Work closely with product and engineering daily. This role sits at the intersection.
• Talk to end users when needed. Sometimes the best way to understand a workflow is to hear it described by the person who does it every day. You should be comfortable with that kind of conversation.
• Participate in sprint planning, standups, and retrospectives.
• Ask good questions. Surface issues early. Be clear about what you know and what you are still figuring out.

Who You Are

The people who do well in this kind of role tend to share a few things in common:

• They are detail-oriented in a way that is genuinely useful, not just nitpicky. They catch the things that would cause problems downstream.
• They write clearly. Their specs are structured, unambiguous, and easy for an engineer to act on.
• They are curious about how systems work, both the regulatory processes and the technology that supports them. They have a real interest in AI and agentic systems, even if they are still early in learning about them.
• They are comfortable asking a lot of questions, especially early on. They would rather clarify something upfront than guess and get it wrong.
• They take ownership of their work. When a spec is incomplete, they go find the missing pieces rather than flagging it and waiting.
• They are comfortable wearing different hats. Some days that means heads-down spec writing, other days it means getting on a call with an end user to understand how they actually process a permit application.
• They are ready to ramp up. There is a lot of domain-specific knowledge in this role and we are happy to help the right person get up to speed, but they need to be motivated to learn quickly.
• They are comfortable using AI tools to research, draft, and organize their work.

Qualifications

Required

• 1-3 years of professional experience in a technical analyst, business analyst, requirements engineer, or similar role. We are open to candidates earlier in their career if the fundamentals are strong.
• Strong writing skills. This role produces a lot of written output and it needs to be clear, organized, and precise.
• Ability to read and understand technical documentation, data models, and system architecture at a conceptual level.
• Comfort working with technical teams and translating between business/regulatory context and engineering requirements.
• Genuine interest in AI, ML, or agentic systems. You do not need a background in these areas, but you should be excited about working on products that use them.
• Demonstrated comfort using AI tools (e.g., Claude, ChatGPT, Copilot, or similar) in daily work.

Big Pluses

• Familiarity with environmental regulations, permitting processes, or compliance workflows.
• Experience working with government agencies or govtech products.
• Exposure to Agile development processes and tools like Linear, Jira, or similar.
• Basic familiarity with databases, APIs, or data formats (JSON, CSV, etc.). Not engineering-level, but enough to read a schema or follow an API call.
• Coursework, projects, or self-directed learning in AI/ML, data science, or related areas.
• Experience working in a startup or small-team environment.

What We Offer

• Competitive salary and health benefits, including major medical, dental, and vision.
• Hybrid position with flexible work hours.
• A small, collaborative team that cares about the work and treats each other well.
• A chance to learn a specialized domain (environmental data, regulatory tech) with real depth.
• Direct exposure to agentic AI product development, from workflow analysis through to automation.
• Meaningful problems: the work directly supports government agencies managing environmental and public health data.

Powered by JazzHR