Role Description
Forward Deployed Engineer (FDE):
Role Purpose
Hands-on engineer who rapidly translates Gemini Enterprise capabilities into working prototypes and deal-specific proof points, owning the technical validation. Builds agentic workflows, lightweight integrations, and multi-modal demonstrations using Gemini APIs, Vertex AI, and Google Cloud to validate feasibility and accelerate customer decisions. Combines strong prompt engineering and Google Gemini ADK with applied analytics, translating prototype outcomes into value narratives.
Must-Have Skills and Experience
- Strong hands-on engineering skills with experience building prototypes, integrations, or solution accelerators using cloud and API-based technologies.
- Experience with Gemini APIs, Vertex AI, Google Cloud, prompt engineering, or similar AI application environments.
- Ability to develop agentic workflows, lightweight integrations, and multi-modal demonstrations for customer or partner scenarios.
- Strong communication and cross-functional collaboration skills with the ability to connect technical validation to business value.
- Total experience: 2 to 5 years, including 1 to 3 years of AI experience, with strong written and spoken English.
- Bachelor’s degree in Engineering or Computer Science.
Preferred Skills
- Google Professional ML Engineer certification is preferred.
- Gemini Enterprise Partner Certification preferred.
- Google Associate Cloud Engineer certification preferred.
- Applied analytics experience and the ability to convert prototype outcomes into clear value narratives are prefer.
Salary Range: $120,000-$130,000 a year
Location Milford, OH Job Function TECHNOLOGY Role Engineer Job Id 422223 Desired Skills Artificial Intelligence | API(Application programming interface) Salary Range $120,000-$130,000 a year Desired Candidate Profile Qualifications : Bachelor of Information Systems
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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