AI Agent Deployment Engineer

Role: Agent Deployment Engineer

Location: SFO and NY / NJ
Number of Roles: 4 - 2 in East Cost and 2 in West Cost
Duration: 6+ Month

About the Role

As an Agent Deployment Engineer, you will be responsible for end-to-end execution of AI agent builds for strategic customers. This is a highly technical delivery role where you will own the implementation work required to launch and scale enterprise-quality agents, partnering with customers and internal teams to define success, translate requirements into build plans, and deliver agents that meaningfully impact the customer’s business.

You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM teams to create tight feedback loops: executing builds, surfacing gaps, and influencing the evolution of agent-building platform based on real customer needs.

This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on execution with structured thinking.

Responsibilities

In this role, you will:

• Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation, and production deployment.
• Design and engineer the core agentic logic governing agent behavior, applying engineering principles to optimize quality, reliability, and correctness across non-deterministic model outputs.
• Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant, and predictable agent performance across real-world scenarios.
• Architect, build, and test integrations with customer systems (e.g., data pipelines, CRMs, ticketing systems), including building the tools, APIs, and workflows needed for reliable deployments at scale.
• Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines.
• Diagnose, debug, and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs, and model behavior.
• Design evaluation and regression-testing frameworks to validate agent behavior against ground truth and guard against performance drift.
• Translate customer needs into clear internal documentation and run tight feedback loops with Engineering to drive platform improvements.
• Partner closely with APMs, Engineering, Design, and Go-To-Market teams to deliver consistent, repeatable, best-in-class agent builds.

Required Qualifications

Your background looks something like this:

• Have 5+ years of relevant experience in a technical customer-facing role (e.g., solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical product/PM, or similar).
• Strong technical foundation: comfortable writing code, working with APIs, and building/validating integrations end-to-end.
• Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration.
• Ability to communicate clearly with senior technical stakeholders, translate requirements into implementation plans, and drive delivery.
• Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them.

Preferred Qualifications

Even better if you have:

• Experience building with or around LLMs / AI agents (prompting, evaluation, guardrails, tooling, workflow design, etc.).
• Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and associated security/compliance considerations.
• A Computer Science, Engineering, or Math degree, or equivalent technical experience.
• Strong product instinct: ability to write crisp PRDs, define success metrics, and contribute customer insight back into product roadmap.