Job Summary

Technical Expert

Skills

- AI-ML

- Python

- ML/NLP frameworks (PyTorch, TensorFlow, Hugging Face, etc.)

- Cloud Platforms(AWS, Azure or GCP)

- Monitoring/observability tools (Prometheus, Grafana, ELK)

Experience

- 6-10 years of progressive work experience in IT

- Hands-on experience in AI/ML engineering, plus experience in SRE, DevOps, or production operations.

- Strong programming skills in Python (plus Go/Java is a bonus).

- Experience with ML/NLP frameworks (PyTorch, TensorFlow, Hugging Face, etc.).

- Experience with distributed systems, APIs, and microservices.

- Hands-on experience with monitoring/observability tools (Prometheus, Grafana, ELK).

- Familiarity with cloud platforms (AWS, Azure, or GCP).

- Experience building AI copilots or autonomous agents for IT operations (AIOps).

- Knowledge of LLMs, retrieval-augmented generation (RAG), and embeddings.

- Experience with event-driven architectures and streaming platforms (Kafka).

- Familiarity with runbook automation and infrastructure-as-code tools.

- Background in high-scale production environments.

Responsibilities

- AI-Driven Toil Elimination - Build AI agents and models to automate alert triage, deduplication, and prioritization.

- AI-Driven Toil Elimination - Develop intelligent ticket classification, routing, and auto-resolution systems.





- AI-Driven Toil Elimination - Design NLP-based systems to interpret logs, runbooks, and incident history.

- AI-Driven Toil Elimination - Implement AI-powered root cause analysis and anomaly detection.

- AI-Driven Toil Elimination - Create self-healing systems that automatically execute remediation actions.

- SRE for AI Systems - Ensure high reliability and availability of automation systems handling production incidents.

- SRE for AI Systems - Define SLIs/SLOs specifically for automated resolution systems (e.g., auto-resolve rate, false positives).

- SRE for AI Systems - Design secure automation with guardrails, fallbacks, and human-in-the-loop controls.

- SRE for AI Systems - Implement robust incident response pipelines integrating AI decision-making.

- SRE for AI Systems - Conduct post-incident reviews focusing on further automation opportunities.

- Operational Intelligence Platform - Build unified observability pipelines (logs, metrics, traces) for AI consumption.

- Operational Intelligence Platform - Develop knowledge graphs or embeddings from historical incidents and runbooks.

- Operational Intelligence Platform - Integrate AI systems with ITSM tools (ServiceNow, Jira, PagerDuty, incident.io etc.).

- Operational Intelligence Platform - Enable continuous learning systems that improve from past incidents.

📌 Technical Expert (Pune)
🏢 VOLKSWAGEN GROUP DIGITAL SOLUTIONS PRIVATE
📍 Pune