Job description

🌎 The Opportunity In the next 30 years, the world will transform every part of the built environment to be climate positive green infrastructure. But today’s renewable energy development process can’t move fast enough to meet global goals. Paces exists to change that. We are providing software and services to accelerate power development - unlocking one of the greatest opportunities of our time: transforming how infrastructure gets built and ensuring it’s built with renewable energy. 🛠️ Our Solution Paces is building the development engine for renewable infrastructure and power projects. We have built Agentic AI that automates early-stage due diligence and pairs it with in-house expertise to accelerate late-stage diligence. The result: projects move from siting to construction-ready in a fraction of the time. Our platform streamlines siting, interconnection, and permitting for renewable energy and data center developers, real estate firms, EV charging companies, and more. 🧑‍🎨 Our Team We are building a team where people can proudly say their time at Paces is the most impactful, meaningful work of their career. Our amazing team in Brooklyn , New York includes incredible team members from tech companies like Meta AI, DeepMind, and Tesla; various high growth startups; as well as industry leaders from TotalEnergies, Con Edison and GE. We are looking for exceptional talents to join our growing Software Engineering team. You will be working closely with power and permitting industry experts to automate power development! 🏆 What You’ll Achieve • Research, prototype, and ship core parts of the geospatial engine at the heart of Paces — large-scale spatial search and analysis that energy developers depend on. • Take open-ended, hard problems in computational geometry and performance — over tens of millions of parcels and nationwide infrastructure data — from prototype to production. • Work across the full spatial stack: DuckDB, Arrow/GeoArrow, file-based spatial indexing, and a OLTP-backed data lake. • Explore the frontier of geospatial computation — for example geospatial embeddings and foundation models (e.g. Clay) — and decide what's worth bringing into the product. • Set the bar for correctness and performance on a system where wrong or slow answers carry real cost. 📈 Requirements • 4+ years of experience building data intensive software in a similar role • Strong computer-science fundamentals: data structures, algorithms, graph theory, and a feel for where time and memory go. • Fluency in a systems/backend language. • A track record of building performant, correct backend systems — you can reason about a hot path and read a query plan. • Experience with DuckDB, Apache Arrow, or comparable columnar/analytical data systems. • A research mindset: comfort with open-ended problems, prototyping to learn, and knowing when to harden a prototype into a production system. • Comfort owning ambiguous problems end-to-end and communicating tradeoffs clearly in writing. ✨ About You You will thrive in our culture if you: • Correctness and performance matter to you. You measure before you claim, document your tradeoffs, and prefer a loud failure to a plausible wrong answer. • You have real depth in the fundamentals and reach for the right primitive, not the familiar one. • You operate with high agency — you scope ambiguous problems, decide, and own the outcome. • You're pragmatic: you ship the simplest thing that solves a real problem. 🚀 Bonus Points • Experience with a systems language — Rust, C, C++, Zig, or similar. • A geospatial / GIS background: PostGIS, GDAL/raster drivers, GeoArrow, projections and coordinate systems, or computational-geometry libraries (GEOS, georust/geo). • ML, embeddings, or geospatial foundation models (e.g. Clay). • Familiarity with zarr / GeoZarr or other large-scale array/raster formats. • Large-scale spatial pipelines, spatial indexing, or distributed/ephemeral compute. • Open source contributor. 💰 Compensation and Benefits • $150K - $220K annual compensation • Competitive equity compensation • 401(k) matching • Health, Dental and Vision insurance • Paid company holidays & PTO • Hybrid work in the office in Williamsburg, Brooklyn ~3x per week ☀️ About Paces • 🛠️ If you’re a builder who wants to actively construct a more climate positive future, join us! • 🗺️ We are enabling the climate optimum use for all the world’s land and are thought leaders in the evolving data center and renewables markets. • 🐶 We have a dog calendar and have dogs running around in the office. • 🌞 We have world class customers and are growing! • 📢 We've raised $18M+ led by Navitas Capital , Resolute Ventures and Y Combinator .

Requirements

Must-haves

Our Solution
4+ years of experience building data intensive software in a similar role
Strong computer-science fundamentals: data structures, algorithms, graph theory, and a feel for where time and memory go.
Fluency in a systems/backend language.
A track record of building performant, correct backend systems — you can reason about a hot path and read a query plan.
Experience with DuckDB, Apache Arrow, or comparable columnar/analytical data systems.
A research mindset: comfort with open-ended problems, prototyping to learn, and knowing when to harden a prototype into a production system.
Comfort owning ambiguous problems end-to-end and communicating tradeoffs clearly in writing.
You will thrive in our culture if you:
Correctness and performance matter to you. You measure before you claim, document your tradeoffs, and prefer a loud failure to a plausible wrong answer.
You have real depth in the fundamentals and reach for the right primitive, not the familiar one.
You operate with high agency — you scope ambiguous problems, decide, and own the outcome.
You're pragmatic: you ship the simplest thing that solves a real problem.

Nice-to-haves

Experience with a systems language — Rust, C, C++, Zig, or similar.
A geospatial / GIS background: PostGIS, GDAL/raster drivers, GeoArrow, projections and coordinate systems, or computational-geometry libraries (GEOS, georust/geo).
ML, embeddings, or geospatial foundation models (e.g. Clay).
Familiarity with zarr / GeoZarr or other large-scale array/raster formats.
Large-scale spatial pipelines, spatial indexing, or distributed/ephemeral compute.
Open source contributor.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigorustml

Platform: gem
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto