Senior Deployed AI Engineer – Gemini Enterprise
LocationSão Paulo, Avenida das Nações Unidas, 12901, 11° andar São Paulo
Work modehybrid
Typefull-time
SenioritySenior
Experience3–5 yrs
DepartmentData Engineering
Company size1,001–5,000 people
PostedSep 21, 2026 · 3w ago
Verified live16h ago
At a glanceSummarised by Seekless from the posting.
3–5 years of experience in software engineering or data engineering
Extensive hands-on use of AI tools and LLM-based development over the past year
Strong hands-on experience with the Google AI stack: Gemini models, Vertex AI, and ideally Gemini Enterprise or ADK
Experience taking at least one solution to production on GCP
Strong programming skills in Python and TypeScript/JavaScript
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
Hands-on experience with at least one agentic framework (Claude Agent SDK, LangGraph/LangChain)
Strong working experience with GCP
Fluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor
Experience building and maintaining data pipelines
Professional English proficiency (C1/C2 minimum)
Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience
Google Cloud certification (to be obtained within first 2 months if not held)
Google Cloud Professional Machine Learning Engineer certification (preferred)
Google Cloud Generative AI Leader certification (valued as foundation)
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
Skills
TypeScript
React
Python
Node
Gemini models
Vertex AI
Agent Development Kit (ADK)
Agent Engine
Gemini Enterprise
Agent Designer
A2A protocol
MCP
Vertex AI Search
RAG Engine
Google Search
BigQuery
GCP
Azure
AWS
Docker/containers
serverless
infrastructure-as-code
Claude Code
Gemini CLI
Codex
Cursor
LangGraph
LangChain
Claude Agent SDK
Terraform
CI/CD
LangSmith
Langfuse
promptfoo
Benefits
Meal (vr)
Free office (work from home or anywhere you want!)
Gympass
Life insurance
Health insurance
Dental insurance
Bi monthly meetings (get together)
Woba (coworking spaces)
Semi annual evaluations (with opportunities for promotion)
About Artefact
Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.
We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions.
As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption.
The Role:
Artefact is looking for 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 will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the front end, the service behind it, the data and retrieval pipelines feeding it, the deployment, and the evaluations proving it works.
This role combines deep, certified expertise in Google’s enterprise AI stack (Gemini models, Vertex AI, and the Gemini Enterprise agent platform) with the ability to deliver end to end. Beyond your platform specialization, you will be expected to work confidently across the full delivery lifecycle — full-stack development, data engineering, cloud infrastructure, evaluation, and client communication.
You will work closely with our clients, with direct exposure from the start, and you will support the professional development of the engineers around you.
Responsibilities
What You’ll DoBuild Full-Stack AI Applications, End to EndYou will build AI products across the entire stack, from interface to infrastructure.
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Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node.
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Implement agentic behavior: orchestration, tool and function calling, memory, and guardrails.
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Build retrieval-augmented generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid search.
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Connect AI systems to enterprise data and applications via APIs, semantic layers, and protocols such as MCP.
Go Deep on Gemini Enterprise and the Google AI StackYou will be the team’s reference for Google’s enterprise AI platform.
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Design and build agents with Gemini models, Vertex AI, the Agent Development Kit (ADK), and Agent Engine.
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Implement and configure Gemini Enterprise for clients: Agent Designer for natural-language and trigger-based agents, the Inbox for managing long-running agents at scale, and agent sandboxes for autonomous problem-solving.
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Connect Gemini Enterprise to the client’s application landscape through first-party and partner connectors, with proper permissions, governance, and auditability.
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Build grounded, retrieval-backed applications with Vertex AI Search and RAG Engine, grounding with Google Search, and BigQuery as the data backbone.
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Implement agent interoperability through the A2A protocol and MCP.
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Track Google’s releases closely and translate new capabilities into client value quickly.
Make AI Systems Production-GradeOur standard is production quality: systems that are reliable, monitored, and maintainable.
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Write evaluation suites and regression tests for LLM-powered features, and monitor cost, latency, and quality in production.
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Apply solid engineering practice: version control, code review, automated testing, CI/CD, and observability.
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Deploy on cloud infrastructure (GCP, Azure, or AWS) using containers, serverless, and infrastructure-as-code.
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Build and maintain the data pipelines that feed AI systems, across warehouses, lakehouses, and vector stores.
Work AI-Natively and Client-FacingOur engineers work AI-natively and represent Artefact directly with clients.
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Use agentic coding tools (Claude Code, Gemini CLI, Codex, Cursor) daily, with good judgment about verification and review.
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Communicate progress, trade-offs, and blockers clearly to clients and project leads.
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Support pre-sales when needed: scope solutions, build demos, and estimate effort with our partnership and consulting teams.
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Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards.
Requirements
What We’re Looking ForRequired Experience
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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).
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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.
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Strong programming skills in Python and TypeScript/JavaScript, and experience building and consuming APIs.
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Experience with front-end development (React or similar) and at least one backend framework.
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Hands-on experience with RAG, embeddings, and vector search, and with at least one agentic framework (Claude Agent SDK, LangGraph/LangChain).
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Strong working experience with GCP; Azure or AWS is a plus
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Fluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor.
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Experience building and maintaining data pipelines.
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Professional English proficiency (C1/C2 minimum) — mandatory. You will work daily with international clients and colleagues.
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Bachelor’s or Master’s degree in computer science, engineering, or a related field, or equivalent practical experience
CertificationsA 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.
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Google Cloud Professional Machine Learning Engineer (preferred), covering Vertex AI, generative AI, and production ML.
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Google Cloud Generative AI Leader is valued as a foundation, complemented by hands-on Vertex AI / Gemini Enterprise delivery experience.
Preferred Experience
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Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling (LangSmith, Langfuse, promptfoo).
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Experience with Terraform or CI/CD pipelines.
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Experience with GCP, BigQuery, or Google Workspace integrations alongside Gemini Enterprise.
Key CapabilitiesA strong candidate will bring:
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Deep expertise in Gemini Enterprise and the Google AI stack, combined with breadth across the full stack
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Owns features end to end, from interface to infrastructure
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Cares about evaluation and reliability, not just the happy path
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Communicates clearly with clients in demos, documents, and code review
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Client-facing mindset: understands client needs and translates business requirements into technical solutions
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Learns new tools and models fast, and shares what works
What We Offer:
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Meal (VR)
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Free Office (work from home or anywhere you want!)
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Gympass
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Insurance: Life, Health, and Dental
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Bi-monthly Meetings (our “Get Together” where we meet to be together, with workshops, lectures, training, and a happy hour!)
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Woba (you can book coworking spaces anywhere you want!)
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Semi-annual evaluations (with opportunities for promotion)
Why you should join us
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Artefact is the place to be: come and build the future of marketing
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Progress: every day offers new challenges and new opportunities to learn
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Culture: join the best team you could ever imagine
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Entrepreneurship: you will be joining a team of driven entrepreneurs. We won’t give up until we make a huge dent in this industry!
Come join us!