Product Manager, Risk Automation

Paces•New York, NY

4h•Hybrid

About The Position

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. Paces is building the development engine for power projects and renewable infrastructure. 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 is projects that move from siting to construction-ready in a fraction of the time. Our platform supports renewable energy and data center developers, real estate firms, EV charging companies, and more by streamlining siting, interconnection, and permitting. 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. Paces is growing rapidly and looking for motivated, collaborative, and insightful individuals to work with our team to develop new products and evolve existing products. Our development timelines are aggressive and you will be asked to rigorously explore solutions for previously unsolved problems. Ideal candidates for our team have passion for making things work, are highly detail-oriented self-starters, and are hungry to do work that matters.

Requirements

4+ years of product management, software engineering, or AI/ML engineering experience.
1+ years of early-stage startup experience, ideally in AI or vertical SaaS.
Deep familiarity with modern LLMs (GPT-4, Claude, Gemini, Llama, etc.) and practical experience applying them to automate manual workflows.
Hands-on experience designing, prototyping, or shipping products using generative AI, agentic AI, or LLM-based automation—whether through fine-tuning, prompt engineering, RAG, multi-agent systems, or tool use.
Proven ability to lead cross-functional teams through ambiguous 0→1 product work, from initial prototype to scaled production system.
Strong understanding of vertical AI business models, including how to price AI services, structure value capture, and navigate the evolving landscape of foundation model capabilities.
Technically fluent—comfortable working with APIs, model outputs, databases, evaluation frameworks, and engineering tradeoffs.
Skilled at making decisions under uncertainty about which approaches to pursue, when to pivot, and how to adjust quickly based on customer feedback and model performance.
Experience balancing rapid experimentation with production quality, reliability, and technical debt.
A problem-solver and team leader who synthesizes complex domain knowledge, AI capabilities, and customer needs into clear product direction.
A fast learner who can pick up new regulatory, environmental, and technical concepts incredibly quickly—and immediately see how AI can automate them.
Scrappy with a strong bias to ship—willing to prototype yourself using LLMs and vibe coding, jump on customer calls to observe manual workflows, or dig into messy documents.
Commercially minded, always connecting automation opportunities to revenue impact, cost savings, and customer willingness to pay for workflow transformation.
Ruthlessly protective of your team's focus and highly selective about adding process.
Deeply excited about the intersection of AI, energy infrastructure, and accelerating clean energy deployment through intelligent automation.

Nice To Haves

Former founder or experience building 0→1 AI products, especially vertical AI applications in regulated industries.
Background in real estate development, renewable energy, environmental consulting, permitting, or adjacent regulated domains.
Comfortable prototyping with Python, AI tools, agent frameworks, or working directly with unstructured documents and geospatial data.
Write regularly and maintain a strong perspective about the future of AI, energy, or infrastructure (blog, Substack, etc.).

Responsibilities

Lead a cross-functional team of software engineers, AI engineers, and solutions engineers (domain experts in environmental, permitting, and site design) to build agentic AI systems that automate critical project risk workflows.
Design and ship vertical AI products that transform manual permitting, environmental review, and site design processes into automated, AI-driven workflows.
Own the product roadmap for risk automation, making strategic decisions on which LLMs, agents, and AI architectures to deploy for maximum impact on development timelines and accuracy.
Research new risk domains quickly, partner with world-class project developers, and turn insights into product direction that delivers measurable ROI.
Work directly with customers to identify high-impact manual workflows, rapidly prototype solutions, and iterate based on real-world performance and feedback.
Partner with leadership to define positioning, pricing, and go-to-market strategies for vertical AI services.
Prioritize ruthlessly between speed, scope, and value while separating signal from noise in complex regulatory and critical infrastructure domains.
Bridge technical execution, domain expertise, and commercial strategy, to keep software engineers and domain specialists organized and working efficiently.