Artefact US
Senior Forward Deployed AI Engineer (Gemini Enterprise)
Build and deploy full-stack AI applications for enterprise clients using Google's AI stack, including Gemini models, Vertex AI, and agentic systems, from frontend to production deployment.
- Compensation
- Not disclosed
- Location
- Remote
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 3–5 years of experience in software engineering or data engineering, with extensive hands-on use of AI tools and LLM-based development over the past year (professional projects, internal initiatives,
- Professional English proficiency (C1/C2 minimum) — mandatory. You will work daily with international clients and colleagues.
- Strong hands-on experience with the Google AI stack: Gemini models, Vertex AI, and ideally Gemini Enterprise or ADK — ideally with experience taking at least one solution to production on GCP.
- Strong programming skills in Python and TypeScript/JavaScript, and experience building and consuming APIs.
- Experience with front-end development (React or similar) and at least one backend framework.
- Hands-on experience with RAG, embeddings, and vector search, and with at least one agentic framework (Google ADK, LangGraph/LangChain).
- Strong working experience with GCP; Azure or AWS is a plus.
- Fluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor.
- Experience building and maintaining data pipelines.
- Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience.
Nice to have
- Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling (LangSmith, Langfuse, promptfoo).
- Experience with Terraform or CI/CD pipelines.
- Experience with GCP, BigQuery, or Google Workspace integrations alongside Gemini Enterprise.
Full description
A Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack: an engineer who works embedded with our clients and takes AI products from idea to production.
You'll design and build the interfaces, services, and agentic systems at the heart of our client work: conversational apps over enterprise data, agents automating workflows, and the pipelines supporting them. You own components end to end: front end, service, data, deployment, and evals.
Build Full-Stack AI Applications, End to End
- Develop interfaces in TypeScript/React and backend services/APIs in Python or Node.
- Implement agentic behavior: orchestration, tool/function calling, memory, guardrails.
- Build RAG pipelines: ingestion, chunking, embeddings, vector/hybrid search.
- Connect AI systems to enterprise data via APIs, semantic layers, and MCP.
Go Deep on Gemini Enterprise and the Google AI Stack
- Build agents with Gemini models, Vertex AI, ADK, and Agent Engine.
- Configure Gemini Enterprise: Agent Designer, the Inbox, and agent sandboxes.
- Connect Gemini Enterprise to client systems via connectors, with proper permissions.
- Build grounded apps with Vertex AI Search, RAG Engine, Search grounding, and BigQuery.
- Implement interoperability via A2A and MCP.
- Track Google's releases and translate new capabilities into client value.
Make AI Systems Production-Grade
- Write evals and regression tests; monitor cost, latency, and quality.
- Apply solid practice: version control, review, testing, CI/CD, observability.
- Deploy on GCP/Azure/AWS using containers, serverless, and infra-as-code.
- Build and maintain data pipelines feeding AI systems.
Work AI-Natively and Client-Facing
- Use agentic coding tools (Claude Code, Gemini CLI, Codex, Cursor) daily, with good judgment.
- Communicate progress, trade-offs, and blockers to clients and leads.
- Support pre-sales: scope solutions, build demos, estimate effort with partners.
- Mentor engineers; contribute to accelerators and engineering standards.
Required Experience
- 3–5 years of experience in software engineering or data engineering, with extensive hands-on use of AI tools and LLM-based development over the past year (professional projects, internal initiatives, or substantial personal builds).
- Professional English proficiency (C1/C2 minimum) — mandatory. You will work daily with international clients and colleagues.
- Strong hands-on experience with the Google AI stack: Gemini models, Vertex AI, and ideally Gemini Enterprise or ADK — ideally with experience taking at least one solution to production on GCP.