Forward Deployed Engineer (Implementation Engineering)

Harness•Chicago, IL

9d•$170,000 - $200,000•Remote

About The Position

Forward Deployed Engineers work embedded inside enterprise engineering teams to design and build AI-native automation on the Harness platform. This is a hands-on, code-first role. You will write production code and scripts, build production pipelines, and connect Harness AI Agents into a customer's existing systems, staying engaged until the capability is live in production. You will work directly alongside customer engineers, turning business objectives into working software rather than documentation or advice. About the role Embed inside a customer's engineering organization for the length of a build engagement to design and build agent-driven automation across the software delivery lifecycle. Write production code connecting Harness AI Agents to a customer's pipelines, repositories, ITSM tooling, security systems, and infrastructure. Partner directly with customer engineering stakeholders and the broader Harness delivery team to translate an approved plan into working software. Prototype quickly, ship incrementally, and iterate directly with customer engineers rather than handing off a static design document. Turn what you build into reusable patterns and share them with the broader Harness delivery organization. Bring direct feedback to Harness product and engineering teams based on what you learn building in real customer environments. Support the transition from custom build to steady-state operation so the customer can independently operate and extend what you built What Success Looks Like: -A working, production agent integration lives in the customer's environment by the end of the engagement. -A reusable pattern or template captured in the Solutions Factory as a direct result of the build. -Customer engineering stakeholders are able to operate and extend the integration without an ongoing Forward Deployed Engineer presence. -Healthy, ongoing customer adoption of the Harness platform and AI Agents beyond the specific build, achieved by working closely with the customer throughout the engagement rather than handing off at go-live.

Requirements

A platform engineering or software engineering background, with hands-on coding, scripting, and integration ability, not configuration-only experience.
Comfortable working directly in a customer's codebase, infrastructure workflows, and CI/CD frameworks.
Experience building integrations against APIs, event-driven systems, or LLM and agent orchestration frameworks.
Prior experience in a forward-deployed, solutions engineering, architecture, or embedded consulting capacity where success was measured by working software, not documentation or advisory output.
Strong grounding in CI/CD and infrastructure-as-code, plus depth in at least one adjacent domain, such as security, observability, or cost management, sufficient to reason about where an agent should plug into a customer's software delivery lifecycle.
Comfortable operating with ambiguity: able to work from a business objective and an agent's capability boundary to a working integration without a pre-written specification.
Excellent stakeholder communication, able to work day to day with customer engineers while keeping internal stakeholders aligned on progress.

Responsibilities

Embed inside a customer's engineering organization for the length of a build engagement to design and build agent-driven automation across the software delivery lifecycle.
Write production code connecting Harness AI Agents to a customer's pipelines, repositories, ITSM tooling, security systems, and infrastructure.
Partner directly with customer engineering stakeholders and the broader Harness delivery team to translate an approved plan into working software.
Prototype quickly, ship incrementally, and iterate directly with customer engineers rather than handing off a static design document.
Turn what you build into reusable patterns and share them with the broader Harness delivery organization.
Bring direct feedback to Harness product and engineering teams based on what you learn building in real customer environments.
Support the transition from custom build to steady-state operation so the customer can independently operate and extend what you built.