Position Overview

Senior / Staff Software Engineer. Direct hire. Fully remote, open to candidates in the Mountain time zone and west.

This is a founding-team engineering role for a highly autonomous senior or staff engineer who owns whole systems and, above all, ships. You will be one of a small number of engineers building a next-generation AI-native intelligence platform: a data ingestion and enrichment pipeline that turns disparate scientific, technical, and market sources into a canonical, tagged, client-facing view of the emerging-technology landscape.

The team is deliberately small and senior. There is no engineering manager between you and the work. You report to the CTO and partner directly with the platform architect and a lean group of engineers. The team is built from people who set their own bar, take direction once and carry it through, and deliver predictably without being managed to it. If you want scope, trust, and to see your work in customers' hands quickly, this is that role.

You do not need to have built exactly this before. What matters is that you have solved adjacent hard problems at data-heavy or AI-driven companies and can bring that experience to bear here. The stack today is Go and Python services moving onto managed cloud infrastructure, and you should expect to learn parts of it as you go.

Responsibilities

Turn messy data into trustworthy signal

• Own systems that take in disparate, inconsistent, real-world sources and turn them into clean, connected, trustworthy data that products and customers can rely on.
• Make the hard calls that come with data at scale: how to model it, how to keep it consistent and deduplicated, how to evolve it over time, and how to keep it honest about what is complete and what is not.

Build AI-native systems

• Build the systems that apply AI to that data: extraction, search and retrieval, classification and enrichment, and the workflows that turn model output into something people can trust and act on.
• Design for quality, including human review and evaluation where it matters, so the platform improves over time rather than drifting.

Own systems end to end on modern cloud

• Take features and services from problem framing through production on cloud-native infrastructure, and keep them reliable, observable, and secure.
• Make pragmatic build-versus-buy decisions, leaning on managed services where they fit and reserving custom engineering for what genuinely differentiates the product.

Raise the bar for how the team works

• Help set the engineering standards for a small team: how you test, how you keep systems loosely coupled and easy to change, and how you ship in small, verifiable increments rather than big-bang releases.
• Use AI-assisted development tooling fluently to move quickly from intent to working, tested code, and help the team do the same.

Qualifications

• 8+ years of software engineering experience, with a track record of owning large production systems end to end, ideally on small and senior teams.
• Deep hands-on experience in at least one of: large-scale data platforms, distributed and event-driven systems, or AI and machine-learning products, with the ability to reason across the rest.
• Strong general-purpose engineering skills in a modern backend language such as Go, Python, Java, or C++. The work is primarily Go and Python today, and picking up a new language and stack quickly matters more than already knowing theirs.
• Solid grounding in cloud-native infrastructure, ideally AWS, with the judgment to design systems that are scalable, loosely coupled, and easy to change.
• Real experience with the shape of these problems even if the tools differ: data pipelines and processing at scale, or building with LLMs, embeddings, search, and evaluation. Direct experience is a plus, not a prerequisite.
• Genuine comfort diving into unfamiliar territory. You learn new domains and technologies fast and you enjoy it.
• A demonstrated bias to incremental delivery: shipping a working slice and improving it rather than holding everything back until it is complete.
• A track record of operating autonomously: setting your own priorities and cadence, delivering reliably without close supervision, and taking direction once rather than needing the same feedback twice.
• Fluency with AI-assisted software development and a habit of using it to raise your own throughput and quality.

Qualities of the Successful Candidate

• You own outcomes, not tickets. You take a problem end to end and you do not need to be chased.
• You ship. You would rather prove the loop runs on real data this week than perfect it in isolation for a quarter.
• You are pragmatic about build versus buy, and you hold strong opinions loosely, changing them on evidence.
• You create clarity in ambiguity rather than waiting to be handed it, and you set the bar rather than wait for it to be set for you.
• You want to throw yourself completely into building something exciting and larger than yourself, alongside a small group of people who are exceptional at what they do.

Why Join

You will help build the platform at the center of this business's future, with real scope and real ownership from day one, on a team small enough that your work is visible and consequential. You will work at the intersection of data engineering, AI, and a domain that matters: helping the world's largest companies make better innovation decisions.