Senior Deployed AI Engineer – OpenAI

Avenida das Nações Unidas, 12901,11° andar São Paulosenior

Machine Learning EngineerData

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Quick Summary

Key Responsibilities

orchestration, tool and function calling, memory, and guardrails. Build retrieval-augmented generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid search.

Requirements Summary

Meal (VR) Free Office (work from home or anywhere you want!) Gympass Insurance: Life, Health, and Dental Bi-monthly Meetings (our “Get Together” where we meet to be together, with workshops, lectures,

Technical Tools

Machine Learning EngineerData

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.

Responsibilities

~1 min read

→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.

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.

Nice to Have

~1 min read

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.

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 We Offer

~1 min read

✓Meal (VR)

✓Free Office (work from home or anywhere you want!)

✓Gympass

✓Insurance: Life, Health, and Dental

✓Bi-monthly Meetings (our “Get Together” where we meet to be together, with workshops, lectures, training, and a happy hour!)

✓Woba (you can book coworking spaces anywhere you want!)

✓Semi-annual evaluations (with opportunities for promotion)

Artefact is the place to be: come and build the future of marketing
Progress: every day offers new challenges and new opportunities to learn
Culture: join the best team you could ever imagine
Entrepreneurship: you will be joining a team of driven entrepreneurs. We won’t give up until we make a huge dent in this industry!