AI & Agentic Engineer, Senior

<p>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.</p> <p>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.</p> <p>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.</p> <h3><strong>The Role</strong></h3> <p>Artefact is looking for a Senior AI & Agentic Engineer: a full-stack engineer who takes AI features from idea to production.</p> <p>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 React front end, the Python or Node service behind it, the RAG pipeline feeding it, and the evaluations proving it works.</p> <p>This role combines breadth and depth: the ability to take a feature from front end to cloud deployment, together with strong expertise in at least one major AI platform — Google (Gemini), Anthropic (Claude), or OpenAI.</p> <p>You will work with direct client exposure, and you will support the professional development of the junior engineers around you.</p> <h3><strong>What You'll Do</strong></h3> <h4><strong>Build Full-Stack AI Applications, End to End</strong></h4> <p>You will build AI products across the entire stack, from interface to infrastructure.</p> <ul> <li>Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node.</li> <li>Implement agentic behavior: orchestration, tool and function calling, memory, and guardrails.</li> <li>Build retrieval-augmented generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid search.</li> <li>Connect AI systems to enterprise data and applications via APIs, semantic layers, and protocols such as MCP.</li> </ul> <h4><strong>Make AI Systems Production-Grade</strong></h4> <p>Our standard is production quality: systems that are reliable, monitored, and maintainable.</p> <ul> <li>Write evaluation suites and regression tests for LLM-powered features, and monitor cost, latency, and quality in production.</li> <li>Apply solid engineering practice: version control, code review, automated testing, CI/CD, and observability.</li> <li>Deploy on cloud infrastructure (GCP, Azure, or AWS) using containers, serverless, and infrastructure-as-code.</li> <li>Build and maintain the data pipelines that feed AI systems, across warehouses, lakehouses, and vector stores.</li> </ul> <h4><strong>Work AI-Natively and Client-Facing</strong></h4> <p>Our engineers work AI-natively and represent Artefact directly with clients.</p> <ul> <li>Use agentic coding tools (Claude Code, Gemini CLI, Codex, Cursor) daily, with good judgment about verification and review.</li> <li>Communicate progress, trade-offs, and blockers clearly to clients and project leads.</li> <li>Support pre-sales when needed: scope solutions, build demos, and estimate effor