Posted 2 days ago
Senior Forward Deployed Engineer (Gemini Enterprise)
@ Welcome to the Jungle
Overview
Artefact is hiring a Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack to work embedded with clients and take AI products from idea to production. The role covers full-stack AI application development, RAG and agentic systems, data pipelines, and production-grade evaluation and deployment. Required: 3–5 years of software or data engineering experience, strong Google Cloud/Vertex AI experience, and a Google Cloud certification (obtained within 2 months if not held). Employment is full-time.
Responsibilities:
- Build full-stack AI applications, from interface to infrastructure
- Implement agents and RAG pipelines on Gemini Enterprise and Vertex AI
- Write evaluation suites and deploy production-grade AI systems on GCP
- Work embedded with clients and communicate progress and trade-offs
- Mentor junior engineers and contribute to internal accelerators
Requirements summary:
- 3–5 years of software or data engineering experience
- Hands-on Google AI stack experience, ideally on GCP in production
- Strong Python and TypeScript/JavaScript skills
- Experience with RAG, embeddings, vector search and an agentic framework
- Google Cloud Professional ML Engineer certification preferred, required within 2 months
Tools & skills
Source and dates
Employer career site / ATS feed · greenhouse
- Employer posting date
- 2026-11-04
- First seen by our source
- 2026-11-04
- Source record updated
- 2026-11-04
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 3+ years |
| Hours per week | 40 (estimated) |
| Work setting | Client sites, Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Licences & certifications | Google Cloud Professional Machine Learning Engineer, Google Cloud Generative AI Leader |
| Education | Bachelor’s degree (preferred) |
| Fields of study | computer science, engineering |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Welcome to the Jungle
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Full company description
Artefact is a leading global consulting company dedicated to accelerating the adoption of data and AI to positively impact people and organizations. We specialize in data transformation and data marketing to drive tangible business results across the entire enterprise value chain. Our 1,500 employees operate across 33 offices in 26 countries (Europe, Americas, Asia, Middle East Africa) and we partner with 1000 clients, including 300 major brands like Samsung, L’Oréal, Orange and Sanofi. We provide customized services from strategy to operations: data strategy, data quality and governance, data platforms, AI factories, demand forecasting, data marketing & sales, AI for call centers, Data & AI School, specialized by industry sectors with dedicated consultancy and technology support.
- LinkedIn followers
- 404,916
- People associated on LinkedIn
- 2,591
- Reported office locations
- 19 Rue Richer, Paris, Île-de-France 75009, FR
- 62 Queen Street, 1st floor, London, England EC4V 2, GB
- Centrepoint North Tower, Mid Valley City, Level 27 Penthouse, Kuala Lumpur, Selangor 59200, MY
- Rothenbaumchaussee 80c, Hamburg, 20148, DE
- Stationsplein 32, Utrecht, Utrecht 3511, NL
- Arjan Office Tower, Floor 6 Office 606, 607 & 608, Dubai, AE
- 19 rue Pierre Semard, Paris, 75009, FR
- Calle de Alfonso XII, 8, Madrid, Community of Madrid 28014, ES
- No. 458 Madang Road, Huangpu District, The Roof, Room 201, Building D, Shanghai, China 200002, CN
- Zhonghai International Center, No. 177, Jiaozidadao, Unit R52M, 5th Floor, Block B, Chengdu, Sichuan, CN
- 6A Shenton Way, Level 04-01 OUE Downtown Gallery, Singapore, 068815, SG
- Capital Tower, Angle Main Street et Boulevard Moulay Abdellah Bencherif, 1er étage, N°2, Casablanca, Morocco 20250, MA
- Bechara El Khoury, BDD 1288 bldg., 3rd floor, Beirut, LB
- 10250 Constellation Blvd, Los Angeles, California 90067, US
- 575 5th Ave, New York City, New York NY 10017, US
- Avenida das Nações Unidas, 12901,11°, São Paulo, BR
- 82 Saemunan-ro, Jongno-gu, 19F, S-tower, Seoul, 07327, KR
- 10-46 Avenida Calle 85, Bogota, 110221, CO
- Olaya Street, SADA Premium - SADA Business Centers, Office 305, Riyadh, Al Olaya District 12211, SA
- 102 Mill Square, 12 Plein Street, Stellenbosch, 7600, ZA
- Pune, Maharashtra, IN
- OSO 127, Interior 104 A1, Colonia del Valle Sur, Benito Juárez, Ciudad de Mexico, CP 03104, MX
- Calle de Pallars, 193, Sant Martí 08005, Barcelona, ES
- Lindenallee 41, Essen, North Rhine-Westphalia 45127, DE
- Avenue Arnaud Fraiteur 15/23, 1050 Ixelles, Brussels, BE
- Mermoz VDN rue MZ-97, Immeuble Zanardo, 1er étage,, Dakar, SN
- Business categories
- Business Intelligence
- Internet
- Advertising
- Artificial Intelligence (AI)
- Other recorded names
- LinkedIn Job Wrapping
- Welcome to the Jungle
- Artefact US
- Artefact North America
- Artefact
- Artifact
- Specialties
- Data Marketing
- Digital Marketing
- eCommerce
- AI Technology
- Data Science
- MLOps
- Generative AI
- Data & AI Consulting
- and Agentic AI
- Profile identifies a recruitment agency
- No
- Reported total investment
- 18,841,900
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Artefact is a leading global consulting company dedicated to accelerating the adoption of data and AI to positively impact people and organizations. We specialize in data transformation and data marketing to drive tangible business results across the entire enterprise value chain. Our 1,500 employees operate across 33 offices in 26 countries (Europe, Americas, Asia, Middle East Africa) and we partner with 1000…
| Field | Value |
|---|---|
| Industry | Business Consulting and Services |
| Company size | 1,001-5,000 employees |
| Headquarters | Paris, Île-de-France |
| Organization type | Privately Held |
| Specialties | Data MarketingDigital MarketingeCommerceAI TechnologyData ScienceMLOpsGenerative AIData & AI Consultingand Agentic AI |
| Open jobs on Jobsy | 4 |
| View page |
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.
What You'll Do
Build Full-Stack AI Applications, End to End
You will build AI products across the entire stack, from interface to infrastructure.
- Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node.
- Implement agentic behavior: orchestration, tool and function calling, memory, and guardrails.
- Build retrieval-augmented generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid search.
- 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 Stack
You will be the team's reference for Google's enterprise AI platform.
- Design and build agents with Gemini models, Vertex AI, the Agent Development Kit (ADK), and Agent Engine.
- 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.
- Connect Gemini Enterprise to the client's application landscape through first-party and partner connectors, with proper permissions, governance, and auditability.
- Build grounded, retrieval-backed applications with Vertex AI Search and RAG Engine, grounding with Google Search, and BigQuery as the data backbone.
- Implement agent interoperability through the A2A protocol and MCP.
- Track Google's releases closely and translate new capabilities into client value quickly.
Make AI Systems Production-Grade
Our standard is production quality: systems that are reliable, monitored, and maintainable.
- Write evaluation suites and regression tests for LLM-powered features, and monitor cost, latency, and quality in production.
- Apply solid engineering practice: version control, code review, automated testing, CI/CD, and observability.
- Deploy on cloud infrastructure (GCP, Azure, or AWS) using containers, serverless, and infrastructure-as-code.
- Build and maintain the data pipelines that feed AI systems, across warehouses, lakehouses, and vector stores.
Work AI-Natively and Client-Facing
Our engineers work AI-natively and represent Artefact directly with clients.
- Use agentic coding tools (Claude Code, Gemini CLI, Codex, Cursor) daily, with good judgment about verification and review.
- Communicate progress, trade-offs, and blockers clearly to clients and project leads.
- Support pre-sales when needed: scope solutions, build demos, and estimate effort with our partnership and consulting teams.
- Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards.
What We're Looking For
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).
- 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
Why Join Artefact
At Artefact, data and AI are not abstract strategy topics. They are tools for creating business value, improving organizations, and helping people make better decisions.
You will join a global community of data and AI experts who combine consulting, engineering, data science, marketing, and technology expertise. You will work on complex, high-impact problems with leading organizations and help shape how enterprises adopt AI responsibly and effectively.
We value action, collaboration, learning, client trust, and shared knowledge. We believe that technology only matters when it is used, adopted, and translated into impact.
Our values aren't decorations on a wall — they're how we actually work:
- There is always a way — We're builders and problem-solvers. An idea only counts if it gets executed.
- Client trust is won in the field — We show up, sleeves rolled up, working side by side with our clients.
- If it's not used, it's useless — We build for adoption and impact, not for slide decks.
- If it's not shared, we're not done — Knowledge shared compounds. We invest in each other's growth.
- We learn every day — In a field that moves this fast, standing still means falling behind. We embrace the challenge.
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