Senior Deployed AI Engineer – Gemini Enterprise
About this role
Professionals who thrive on taking AI products from initial concept directly to production will find a natural home in this role. Artefact operates as a next-generation data and AI consulting firm, building practical, measurable enterprise solutions rather than just offering advice. This team specifically embeds engineers directly with clients to design and deploy conversational applications, multi-step agents, and retrieval pipelines using the Google AI stack. The person holding this position will own components completely across the front end, backend services, data pipelines, deployments, and evaluations.
Operating at the intersection of consulting and engineering, the individual will manage direct client exposure from the beginning while also supporting the professional development of nearby teammates. Success here requires a blend of platform specialization in tools like Gemini Enterprise alongside generalist software delivery skills, cloud infrastructure knowledge, and clear communication abilities. Anyone eager to move past experimentation and drive scalable, governed AI adoption across enterprise value chains will do well in this environment.
What you will do
- Build full-stack AI applications across the entire stack from user-facing TypeScript and React interfaces to Python and Node backend services.
- Implement agentic behavior including orchestration, tool and function calling, memory management, and security guardrails.
- Construct retrieval-augmented generation pipelines encompassing data ingestion, chunking, embeddings, and vector or hybrid search.
- Design and configure Gemini Enterprise and Vertex AI solutions for clients utilizing Agent Designer, agent sandboxes, and the Agent Development Kit.
- Write evaluation suites and regression tests for LLM-powered features while monitoring production cost, latency, and reliability.
- Deploy workloads on cloud infrastructure utilizing containers, serverless architectures, and infrastructure-as-code.
- Represent the firm directly with clients by communicating progress and supporting pre-sales activities, demos, and solution scoping.
What you need
- Bring three to five years of experience in software or data engineering with substantial hands-on AI tool and LLM development background over the past year.
- Demonstrate strong practical familiarity with the Google AI stack including Gemini models, Vertex AI, and Gemini Enterprise or ADK.
- Possess solid programming skills in Python and TypeScript or JavaScript alongside experience building and consuming APIs.
- Have hands-on work history with front-end development using frameworks like React alongside at least one backend framework.
- Show direct experience implementing retrieval-augmented generation, embeddings, vector search, and agentic frameworks such as LangGraph or LangChain.
- Maintain strong working knowledge of Google Cloud Platform alongside familiarity with data pipelines.
- Communicate professionally in English at a C1 or C2 level for daily interaction with international clients and colleagues.
- Hold a Bachelor's or Master's degree in computer science, engineering, or a related field, or demonstrate equivalent practical experience.
Nice to have
- Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling like LangSmith, Langfuse, or promptfoo
- Experience with Terraform or CI/CD pipelines
- Experience with GCP, BigQuery, or Google Workspace integrations alongside Gemini Enterprise
- Google Cloud Professional Machine Learning Engineer or Generative AI Leader certification
Benefits
- Meal (VR)
- Free Office (work from home or anywhere you want!)
- Gympass
- Insurance: Life, Health, and Dental
- Bi-monthly Meetings with workshops, lectures, training, and a happy hour
- Woba for booking coworking spaces anywhere
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
Employees have the flexibility to work from home or anywhere they want. The company also provides access to Woba so team members can book coworking spaces anywhere.
What tools and technologies will I be expected to use?
The tech stack centers heavily around the Google AI stack, including Gemini models, Vertex AI, and Gemini Enterprise. Engineers also build with Python, TypeScript, React, Node, vector stores, and agentic development tools.
What are the opportunities for career growth and evaluation?
The firm conducts semi-annual evaluations that provide structured opportunities for promotion. Team members also participate in bi-monthly get-togethers featuring workshops, lectures, and training.
The application is on the official LinkedIn Job Wrapping careers page.
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