Forward Deployed Engineer

Ovii's Interpretation of the Role

The Forward Deployed Engineer builds, ships, and operates production AI applications on enterprise GPT platforms. Embedded in cross‑functional teams, the engineer translates business problems into AI‑enabled solutions and owns the full solution lifecycle from design through ongoing support.

Role Snapshot

• AI solution builder
• Enterprise integration specialist
• Cross‑functional team member
• Production‑grade AI engineer
• Business‑focused technologist

Must-Have Requirements

• AI solution design and production
• Enterprise integration via APIs/webhooks
• Observability and responsible AI controls
• Evaluation approaches (test sets, quality metrics)
• AI solution patterns (RAG, orchestration, model integration, human‑in‑the‑loop)
• Technical roles with stakeholder engagement (Forward Deployed Engineer, Solutions Engineer, Integration Engineer, Automation Engineer)
• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data and Analytics

Nice-to-Have Signals

• Enterprise GPT platforms (Glean, Claude)
• Automation tools (n8n, Zapier, Make)
• Business systems (Salesforce, ServiceNow, SharePoint/Teams)
• Enterprise security concepts (RBAC, least privilege, SSO, SAML, OAuth, OIDC)
• Cross‑functional delivery team experience

Work Setup

• Location: United States, United States
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range details beyond OTE
• Remote eligibility specifics

What You'll Likely Work On

• Design and ship AI agents and multi‑step workflows on GPT platforms using tools such as Agent Builder and MCP
• Apply AI patterns like RAG, orchestration, and human‑in‑the‑loop to solve business friction points
• Integrate enterprise data sources (e.g., Salesforce, ServiceNow, SharePoint) via APIs, webhooks, or automation tools
• Extend platform capabilities with custom services, REST APIs, and context‑aware workflows
• Ensure solutions meet security, reliability, observability, and compliance standards
• Create reusable templates and components for cross‑team reuse
• Prototype, validate with users, and harden MVPs into scalable production solutions
• Own LLM quality, telemetry, and cost optimization through prompt design, guardrails, and usage instrumentation

Good Fit If You Have

• Enjoys direct collaboration with business stakeholders and translating ambiguous needs into concrete AI solutions
• Comfortable operating within a shared‑team model where design, adoption, and outcomes are tightly coupled
• Proactive about surfacing workflow pain points and proposing AI‑driven improvements