Senior Forward Deployed AI Engineer (Gemini Enterprise)

Descripción del puesto

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. 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. Certifications A Google Cloud certification is a strong differentiator at application. If you do not hold one yet, obtaining it within your first 2 months in the role is a requirement — Artefact sponsors the exam and gives you time to prepare. Google Cloud Professional Machine Learning Engineer (preferred), covering Vertex AI, generative AI, and production ML. Google Cloud Generative AI Leader is valued as a foundation, complemented by hands-on Vertex AI / Gemini Enterprise delivery experience. Preferred Experience 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. Key Capabilities A strong candidate will bring: Deep expertise in Gemini Enterprise and the Google AI stack, combined with breadth across the full stack Owns features end to end, from interface to infrastructure Cares about evaluation and reliability, not just the happy path Communicates clearly with clients in demos, documents, and code review Client-facing mindset: understands client needs and translates business requirements into technical solutions Learns new tools and models fast, and shares what works