Forward Deployed Engineer, Applied AI

Parisi Labs; New York (NY); On-site; USD 175,000 - 260,000; Full time

Benefits offered by this job

Equity

Medical benefits

Dental benefits

Job summary

Parisi Labs is seeking a Forward Deployed Engineer to take operator problems from first conversation to delivered technical solutions. The focus is battery-storage owner-operators, building integrations and workflows while advising how solutions can scale for Ask The Grid and core technology.

This engineering role writes production-quality code, works directly with users, and decides which parts of an engagement should become reusable product or infrastructure. Location: NYC area preferred.

Qualifications

• Strong Python, SQL, API and production software experience.
• Experience integrating ML or data-intensive systems into real customer workflows.
• Experience as a forward deployed or customer-facing engineer.

Responsibilities

• Learn operator workflows and translate them into a clear technical plan.
• Build data integrations, internal tools, and applied-AI workflows to solve defined problems.
• Deliver customer-facing technical work from scoping to reliable operation.
• Establish clear success criteria and explain technical results to operators and executives.
• Debug issues with users and turn friction into reusable product, tooling, and docs.
• Identify reusable patterns across engagements without forcing a single implementation.
• Maintain a tight feedback loop among customers, product, data, research, and engineering.
• Earn trust through technical judgment, precise communication, and scoped work.

Skills

Python

SQL

APIs

Production software

Customer-facing engineering

Job description

About Parisi Labs

Parisi Labs is an AI company building learning systems for complex physical environments. We combine historical and live data with real operational context to help people understand the present, evaluate possible futures, and make better decisions.

Energy is our first proving ground. Ask The Grid (https://askthegrid.com) is our public product for exploring the systems, markets, and assets that make up the power grid. We are a small technical team working across machine learning, data infrastructure, software, and real-world operations.

About The Role

We are looking for a Forward Deployed Engineer to take important operator problems from first conversation to working technical delivery.

Our initial focus is battery-storage owner-operators. They make frequent decisions inside a changing market while respecting the physical and commercial constraints of real assets. You will work alongside them, understand how those decisions are made, build the necessary integrations and workflows, and bring what you learn back into Ask The Grid and our core technology.

This is an engineering role, not a pre-sales demo role. You will write production-quality code, work directly with users, and decide which parts of an engagement should become reusable product or infrastructure.

What You Will Own

• Learn how an operator works today and translate that workflow into a clear technical plan.

• Build data integrations, internal tools, and applied-AI workflows that solve the agreed problem.

• Deliver customer-facing technical work from initial scoping through reliable operation.

• Establish clear success criteria and make technical results understandable to operators and executives.

• Debug issues with users while turning repeated friction into better product, tooling, and documentation.

• Identify reusable patterns across engagements without forcing every customer into the same implementation.

• Maintain a tight feedback loop among customers, product, data, research, and engineering.

• Earn trust through technical judgment, precise communication, and disciplined scope.

First 90 Days

• 30 days: Learn Ask The Grid, our initial operator workflows, and the technical path from customer context to a credible implementation plan.

• 60 days: Own a meaningful technical workstream with an operator and ship a working result.

• 90 days: Complete an end-to-end engagement milestone and turn the reusable lessons into product, tooling, or integration improvements.

You May Be A Fit If

• You are a strong software engineer who wants to stay close to users and implementation.

• You can turn an ambiguous operational problem into a concrete system without overpromising.

• You are comfortable with messy data, unfamiliar workflows, and high-trust customer environments.

• You can explain technical results clearly to both engineers and business operators.

• You know when to build something reusable and when a focused implementation is the right answer.

• You have strong judgment about reliability, security, credibility, and customer trust.

• You want significant ownership on a small team rather than a narrow solutions-engineering lane.

Helpful Background

• Forward deployed engineering, customer engineering, implementation engineering, applied AI, data engineering, or product engineering.

• Strong Python, SQL, API, and production software experience.

• Experience integrating ML or data-intensive systems into real customer workflows.

• Experience in battery storage, wholesale power, grid operations, industrial systems, finance, or another operationally complex domain is valuable.

• Experience with internal tools, technical documentation, notebooks, or customer-facing analysis is useful.

• High-slope candidates can fit if their engineering depth and customer judgment are exceptional.

Location And Working Style

New York City is preferred because this role works closely with the CEO and customers. Boston/Cambridge can work for an exceptional candidate with a strong in-person cadence. Regular customer travel is part of the role.

Compensation And Benefits

Base salary range: $175K-$260K, plus meaningful early-stage equity. Parisi Labs provides medical and dental benefits. Final compensation depends on level, location, experience, and role scope.

Interview Process

• Founder conversation with the CEO and CTO.

• Technical working session on a representative operator problem.

• Engineering calibration with the CTO.

• In-person final.

• Offer review.