Forward Deployed Software Engineer

Job Description

Job Description

Forward Deployed Software Engineer

A well-funded, rapidly growing software company is hiring Forward Deployed Engineers to build and deploy production-grade agentic software across a portfolio of operating businesses.

This is not a pre-sales, implementation or prototype-building position. You will identify consequential operational problems, design the technical solution and personally ship the system into production.

You will remain accountable after launch, improving reliability, evaluation quality and autonomy until the software produces measurable business results.

The role combines the ownership of a founding engineer with the customer proximity of a forward deployed engineer. You will move between ambiguous business problems, full-stack development, AI-agent architecture, enterprise integrations and direct conversations with company leadership.

## What you will build

You will create intelligent systems that automate complex operational workflows.

A typical deployment may involve:

* Embedding with an operating company to understand its workflows, systems and constraints

* Identifying the highest-leverage opportunities for applied AI

* Defining the initial technical wedge and measurable success criteria

* Building integrations, agent logic, tools, prompts, evaluations and user interfaces

* Establishing autonomy levels, approval gates and human-in-the-loop controls

* Deploying the system into live operations

* Monitoring performance and investigating failures

* Improving reliability through evaluations, observability and user feedback

* Turning successful deployment patterns into reusable product capabilities

The objective is not to produce an impressive demonstration. It is to build software that people trust enough to use in critical business workflows.

## Technical environment

You should be comfortable owning a system across the entire stack rather than operating within one narrow layer.

The environment includes:

* TypeScript and Python

* React

* SQL

* LLMs and foundation-model APIs

* Agentic workflows and tool-calling systems

* Evaluation frameworks and outcome tracking

* Autonomy gating and human approval controls

* Event-driven systems

* Modern data platforms

* Enterprise APIs and operational integrations

We care more about your ability to make strong architectural decisions and ship reliable systems than whether you have already used every component in the stack.

## What makes this role different

Most AI engineers work several layers away from the problem they are solving. Here, you will see the operational problem directly, determine what should be built and own the result in production.

You will have the freedom and responsibility to:

* Scope technically ambiguous problems without waiting for a complete specification

* Decide where deterministic software ends and agentic behavior begins

* Build evaluations that reflect business outcomes rather than superficial benchmarks

* Determine when an agent can act autonomously and when human approval is necessary

* Design for failure, observability, security and safe recovery

* Work directly with users, operators and executives

* Convert repeated deployment patterns into scalable product capabilities

* Influence the underlying platform through what you learn in the field

You will not spend your time producing decks, conducting generic demonstrations or handing prototypes to another engineering team. You will write production code and own what happens next.

## What we are looking for

You are likely to succeed if you:

* Have approximately three to six years of full-stack, product-engineering or forward-deployed engineering experience

* Have shipped an LLM-powered or agentic system used by real customers

* Can explain how you evaluated its outputs, handled failures and controlled autonomous actions

* Can build across frontend, backend, data and integration layers

* Have strong proficiency in TypeScript or Python, React and SQL

* Have worked in an early-stage or high-growth software environment

* Can translate an unclear operational problem into a focused technical solution

* Enjoy working directly with customers, operators and senior executives

* Communicate clearly without losing technical depth

* Prefer broad ownership over narrowly defined tickets

* Want accountability for business outcomes, not just code delivery

Experience as a Forward Deployed Engineer, founding engineer, product engineer or customer-facing software engineer is valuable, but the exact title is not important. We care about what you personally built and whether it worked in production.

## This role is probably not right for you if

* Your AI experience is limited to hackathons, demonstrations or internal experiments

* You have used AI coding assistants but have not built AI into a production product

* Your experience is exclusively frontend, backend, mobile or ML research

* You prefer receiving completely defined requirements before beginning work

* Your customer-facing experience primarily involves presentations or pre-sales demonstrations

* You want to hand a system off immediately after launch

* You are uncomfortable being accountable for software operating in live environments

* You do not want regular onsite collaboration or travel

## Why consider this opportunity

The company is building a model in which engineers have unusually direct influence over business operations.

A successful system built for one operating company can be converted into a reusable capability across multiple businesses. Your work therefore combines the immediacy of customer deployment with the compounding impact of platform engineering.

The technical patterns are still being established. Engineers joining now will help define how the company discovers opportunities, builds agentic systems, measures performance and scales successful deployments.

This is an opportunity for someone who wants to build consequential software, work close to the customer and see exactly how their engineering decisions affect real-world outcomes.

## Location and working model

The role can be based in New York, San Francisco or Toronto.

Engineers should expect meaningful in-person collaboration and regular domestic travel to operating-company locations, potentially two or three days per week depending on the deployment.

The office expectation is at least three days per week, with four preferred when not working at a customer location.

## Compensation

Base salary: $185,000 to $240,000, plus competitive equity.

Visa transfers and relocation support may be considered.

## Interview process

The interview process includes:

1. Initial conversation

2. Technical screen

3. Two-hour AI take-home exercise

4. Technical discussion covering architecture and engineering tradeoffs

5. System-design and experience interview

The strongest candidates will demonstrate not only that they can build sophisticated AI software, but that they know how to make it reliable, useful and trusted in production.