Senior Deployed AI Engineer – OpenAI

LinkedIn Job Wrapping, Avenida das Nações Unidas, 12901,11° andar São Paulo +1

The role

Artefact is looking for a Senior Deployed AI Engineer specialized in the OpenAI ecosystem: 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 the OpenAI ecosystem (GPT and reasoning models, the OpenAI platform, and its agentic tooling) 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.

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Senior Deployed AI Engineer – OpenAI

LinkedIn Job Wrapping, Avenida das Nações Unidas, 12901,11° andar São Paulo +1

The role

Artefact is looking for a Senior Deployed AI Engineer specialized in the OpenAI ecosystem: an engineer who works embedded with our clients and takes AI products from idea to production.

What you will 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 the OpenAI Platform You will be the team's reference for the OpenAI platform.

Design and build agentic systems on the OpenAI platform: Responses API, Conversations API, and the Agents SDK — including its sandboxed execution environments and harness for long-running, multi-step, multi-tool tasks.
Build, deploy, and optimize enterprise agents and workflow automations with AgentKit and ChatGPT Enterprise (custom GPTs, connectors, admin and governance).
Apply the platform's core building blocks well: function calling, structured outputs, and model selection across GPT and reasoning model families for each cost, latency, and quality trade-off.
Deliver on Azure OpenAI where clients require it, handling enterprise security, networking, and quota management.
Use OpenAI's evaluation and fine-tuning tooling to measure and improve quality in production.
Track OpenAI'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 you need

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 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 (Claude Agent 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.
Professional English proficiency (C1/C2 minimum) — mandatory. You will work daily with international clients and colleagues.
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

Senior Deployed AI Engineer – OpenAI

The role

Senior Deployed AI Engineer – OpenAI

The role

What you will do

What you need

Pay and benefits

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