Job Description:

Only Brazil*

We are looking for a hands-on Senior AI/AIOps Engineer to build the intelligence layer of an enterprise IT Operations/SRE portal. The role requires strong production experience across AI/ML, GenAI, AIOps, Python, observability and Root Cause Analysis (RCA).

Key Responsibilities and Requirements:

- Production AI/ML: Design, develop and support AI/ML systems used by real users in production.

- GenAI/LLM: Hands-on experience with RAG, document chunking, embeddings, vector search, hybrid retrieval, reranking, tool/function calling and structured outputs.

- Agentic AI: Build agents or multi-step AI workflows using LangGraph, LangChain, Semantic Kernel or equivalent. Implement restricted tools, guardrails, human approval and auditable actions.

- AI Evaluation: Create evaluation datasets, measure accuracy and error rates, and improve AI systems based on results. Evaluate RCA and assistant responses using historical incidents.

- AIOps: Build time-series anomaly detection based on normal system behavior. Implement alert deduplication and noise reduction using metrics, logs or events.

- Python: Strong production Python development and automated testing. Experience with Pandas, NumPy and scikit-learn; PyTorch/TensorFlow where relevant.

- Production Troubleshooting: Diagnose incidents across Linux CPU, memory, disk and network; Java heap, GC and thread dumps; and Python services.

- Observability: Hands-on experience with Splunk SPL, dashboards and alerts, plus Prometheus, OpenTelemetry, Dynatrace or equivalent.

- RCA: Build or significantly contribute to RCA, AIOps or incident-analysis systems. Correlate operational signals and events to rank probable causes with supporting evidence.

Additional Experience:

- ServiceNow integration
- Java/Spring Boot
- Kafka or stream processing
- Docker
- CI/CD
- Clear technical documentation

What We Expect:

A hands-on engineer capable of building reliable production AI solutions rather than only prototypes. The engineer should combine GenAI, agentic AI, AIOps, observability and production troubleshooting to develop intelligent capabilities for enterprise IT Operations/SRE environments.