Senior AI Engineer
Promtior · Département Montevideo
Job description
About the role
We are looking for a Senior AI Engineer with deep hands‑on experience building agentic AI systems to join our Engineering team as a technical reference. This senior, client‑facing role will own the technical direction of our agentic solutions end‑to‑end, make and defend architecture decisions in front of clients, and raise the technical level of the engineers around you as we scale our global operation.
Key responsibilities
- Lead the design and development of production‑grade agentic AI systems, defining architecture of autonomous agents, tool orchestration, and retrieval pipelines.
- Establish evaluation and quality practices, including evals, guardrails, observability, and cost/latency optimization, and ensure reliability in production.
- Act as the technical counterpart for clients, translating business problems into agentic solutions and defending the approach to technical stakeholders.
- Mentor and unblock other engineers, review code, and drive adoption of new AI technologies across teams.
- Contribute to the evolution of solutions toward more advanced machine‑learning components.
Required profile
- Advanced or completed studies in Systems Engineering, Data Science, AI, or related fields.
- 5+ years of professional software engineering experience.
- 2+ years of hands‑on experience building and shipping agentic or LLM‑based systems to production.
- Strong production‑level command of Python.
- Proven experience designing agents, tool orchestration, RAG pipelines, and integrating APIs, backend services, and cloud environments (AWS, GCP, or Azure).
- Experience acting as a technical reference, mentoring engineers, and working directly with clients.
Required skills
- Python
- Agentic system design and tool orchestration
- Retrieval‑augmented generation (RAG) pipelines, embeddings, vector databases
- Cloud platforms: AWS, GCP, Azure
- Git and collaborative development workflows
- Docker, containers, CI/CD
- MLOps and model deployment at scale
- Model evaluation frameworks, guardrails, AI observability tooling
- Multi‑agent systems and Model Context Protocol (MCP)
- NLP and text processing
What we offer
- 20 paid days off per year
- Hybrid work model with Flex Days for monthly team activities
- Professional development courses
- Internal clubs (soccer, padel, running, cinema)
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Published 5 hours ago
Expires 1 month from now
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Promtior
Département Montevideo
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