Senior AI & Agentic Engineer

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).
• Professional English proficiency (C1/C2 minimum) — mandatory. You will work daily with international clients and colleagues.
• 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 (LangGraph/LangChain, Google ADK, Claude Agent SDK, or OpenAI Agents SDK).
• Specialization in at least one major AI platform ecosystem — Google (Gemini, Vertex AI, Gemini Enterprise), Anthropic (Claude, Managed Agents, MCP), or OpenAI (Responses API, AgentKit) — and working experience with one cloud platform (GCP, Azure, or AWS).
• 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 certification on at least one major AI platform or cloud is a strong differentiator at application. If you do not hold one yet, obtaining one within your first 2 months in the role is a requirement — Artefact sponsors the exam and gives you time to prepare.

• Examples: Claude Certified Developer – Foundations (Anthropic), Google Cloud Professional Machine Learning Engineer, Google Cloud Generative AI Leader, Microsoft Azure AI Engineer Associate, or equivalent AWS credentials.

Preferred Experience

• Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling (LangSmith, Langfuse, promptfoo).
• Experience with Terraform or CI/CD pipelines.

Key Capabilities

A strong candidate will bring:

• Breadth across the full stack, with depth in at least one AI platform
• Owns features end to end, from interface to infrastructure
• Cares about evaluation and reliability, not just the happy path
• Communicates clearly 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

Projects

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.

What You'll Do

A Senior AI & Agentic Engineer: a full-stack engineer who takes AI features from idea to production.

You'll design and build the interfaces, services, and agentic systems at the heart of our client work: conversational apps, agents automating workflows, and the pipelines supporting them. You own components end to end: React front end, Python/Node service, RAG pipeline, and evals.

This role combines breadth and depth: taking a feature from front end to cloud deployment, plus strong expertise in at least one major AI platform — Google (Gemini), Anthropic (Claude), or OpenAI. You'll have direct client exposure and support junior engineers' growth.

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.

Make AI Systems Production-Grade

• Write evals and regression tests; monitor cost, latency, quality.
• Apply solid practice: version control, review, testing, CI/CD, observability.
• Deploy on GCP/Azure/AWS using containers, serverless, 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.
• Mentor engineers; contribute to accelerators and standards.

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.