Data & AI Operations Engineer.
Responsibilities
- Apply AI/ML/LLM tools to solve operational and reliability challenges
- Prototype and validate AI-driven improvements with measurable outcomes
- Operationalise successful AI use cases into scalable production systems
- Enhance observability, incident detection, and automation in operations
- Support end-to-end lifecycle of AIOps, MLOps, and LLMOps solutions
- Collaborate with engineers and ops teams to align solutions with business needs
- Stay ahead of emerging AI technologies and embed responsible AI practices
- Build prototypes and measure impact with clear metrics, analyze logs, metrics, and events to detect anomalies and automation opportunities.
- Deploy, monitor, and maintain ML/LLM solutions
- Automate repetitive tasks with scripts/workflows. Document solutions and lessons learned for reuse
- Bachelor\'s/Master\'s in Computer Science or related field
- 1–2 years\' experience with Python, SQL, Spark, Docker/Kubernetes, Git, pytest
- Exposure to MLOps/GenAI Ops tools, ML/GenAI projects, or open-source contributions
- Familiarity with monitoring stacks (Prometheus, Grafana, OpenTelemetry)
- Hands-on with cloud ML services (Databricks, Azure ML, etc.)
- Curious, proactive, collaborative, and impact-driven