Senior Forward Deployed AI Engineer (Openai)

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 hands-on experience with the OpenAI ecosystem: Responses API or Agents SDK, function calling, and prompt engineering for GPT and reasoning models — ideally with experience taking at least one solution to production (OpenAI API or Azure OpenAI).
• 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 (OpenAI Agents SDK, LangGraph/LangChain).
• Working experience with at least one cloud platform; Azure experience is a strong plus for Azure OpenAI delivery.
• 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
Certifications are a strong differentiator at application. OpenAI's proctored certification program is still rolling out publicly, so where a formal OpenAI credential is not yet available to you, we expect you to obtain the closest available credential within your first 2 months in the role — Artefact sponsors the exam and gives you time to prepare.

• OpenAI Academy certifications and badges, as they become generally available.
• Microsoft Certified: Azure AI Engineer Associate is highly valued for Azure OpenAI delivery.

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 realtime/voice APIs, multimodal applications, or fine-tuning at scale.

Key Capabilities

A strong candidate will bring:

• Deep expertise in the OpenAI platform, 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

What You'll Do

Artefact is looking for a Senior Deployed AI Engineer specialized in the OpenAI ecosystem: embedded with clients, taking AI products 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 pipelines supporting them. You own components end to end: front end, service, data, deployment, evals.

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.

Go Deep on the OpenAI Platform

• Build agentic systems on OpenAI: Responses API, Conversations API, Agents SDK, incl. sandboxed execution for long-running tasks.
• Build and optimize enterprise agents with AgentKit and ChatGPT Enterprise (custom GPTs, connectors, governance).
• Apply function calling, structured outputs, model selection across GPT/reasoning families per trade-off.
• Deliver on Azure OpenAI where required: security, networking, quota.
• Use OpenAI's eval and fine-tuning tooling to improve quality.
• Track OpenAI's releases and translate capabilities into client value.

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 junior 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.

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.