Forward Deployed Engineer

About the role

This role delivers hands-on technical leadership to turn enterprise pilots into production agent workflows using Warp Oz. You will architect and ship agent solutions alongside customer engineering teams, guiding deployments and integrations that drive real business value. You own the full lifecycle of customer agent implementations from initial discovery through production rollout and optimization. You translate complex customer requirements into robust, scalable agentic workflows that leverage Warp's platform capabilities. You act as a critical bridge between customer needs and the product engineering roadmap, ensuring deployed solutions meet high standards of reliability and performance. You will mentor customer engineers on best practices for agent development and deployment within cloud environments. You continuously refine your own technical and domain expertise to address evolving enterprise challenges in agentic computing.

Key facts

What you'll do

Design sandboxed environments and multi-step agent pipelines that integrate cleanly with current development lifecycles.

Debug agent runs using observability and session-sharing tools to ensure reliable behavior.

Configure and manage self-hosted deployments using Docker, Kubernetes, or direct backend infrastructure.

Provide clear feedback to product and engineering on integration pain points and platform gaps.

Translate field insights into actionable roadmap items that guide the Oz platform evolution.

Implement secure and scalable agent workflows that adhere to enterprise governance and compliance standards.

Conduct technical discovery sessions to understand customer workflows and identify automation opportunities.

Collaborate with sales and success teams to shape solution proposals and proof-of-concept efforts.

Perform root cause analysis on production issues affecting agent reliability and performance.

Document deployment patterns, configurations, and known limitations for internal and external audiences.

Evaluate new infrastructure technologies and assess their fit for agent execution at scale.

Champion best practices for version control, testing, and monitoring in agentic application development.

Support customers through major deployment milestones including rollout, adoption, and optimization phases.

Facilitate knowledge transfer sessions between customer teams and Warp engineering groups.

Continuously iterate on deployment playbooks based on feedback and observed customer behaviors.

Requirements

The posting states a bachelor's degree requirement. Bring FDE-equivalent experience from startups or early-stage companies where you built custom customer solutions.

Comfortably work with Docker, CI/CD pipelines, cloud infrastructure on AWS/GCP/Azure, container orchestration, and Linux.

Understand prompt engineering, agent architectures, tool use, and deployment of AI-powered production workflows.

Communicate effectively with senior engineers and executives while articulating Warp's vision for cloud agents.

Navigate enterprise relationships with patience and adaptability in complex customer environments.

Maintain a strong sense of ownership for customer outcomes and follow through on commitments.

Demonstrate the ability to learn quickly and apply technical concepts to novel problems.

Show resilience and flexibility when operating in fast-paced, ambiguous, and rapidly changing settings.

Practical notes

This role reports to leadership and has direct exposure across all business functions.

You will build solutions with customers rather than only advising them.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

Agentic development tools combine terminal workflows with AI orchestration for software delivery.

Cloud agents, prompt engineering, and production AI workflows are central to this role.

Strong infrastructure and debugging skills help ensure reliable autonomous system behavior.

Cross-functional communication shapes product direction and unblocks enterprise adoption.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.