Hyderabad, Telangana

Job Summary

Role Summary

Key Responsibilities

Key Responsibilities

- Build and maintain production-grade inference pipelines for LLM workloads.
- Design and implement LLMOps pipelines for model, prompt, and configuration lifecycle management.
- Implement monitoring for latency, throughput, cost, errors, drift, and hallucinations.
- Build dashboards and alerts to ensure SLA and reliability targets.
- Optimize inference cost and performance using caching, batching, routing, and autoscaling strategies.
- Enforce security, access control, audit logging, and governance controls for LLM usage.
- Collaborate with Responsible AI teams to operationalize safety and compliance guardrails.
- Enable AI Engineers and Fullstack teams through reusable LLMOps frameworks and platforms.

Skill Requirements

Required Skills & Experience

- Solid understanding of LLMs, Generative AI architectures, and inference workflows.
- Hands-on experience running LLM-based systems in production environments.
- Strong experience with cloud platforms (Azure, AWS, or GCP).




- Hands-on experience with Docker, Kubernetes, and container orchestration.
- Programming and automation skills in Python or similar languages.
- Familiarity with MLOps / LLMOps tooling, monitoring, and logging systems.

Other Requirements

Experience Level

- 14+ years of overall experience in DevOps, Platform, or ML/AI Engineering roles.
- 2-4+ years of experience operating ML or GenAI systems in production.

Success Measures

- Stable, scalable, and cost-efficient LLM systems running in production.
- Reduced production incidents and faster recovery for AI services.
- Faster and safer enterprise adoption of GenAI solutions enabled through robust LLMOps practices.

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📌 Senior Technical Specialist (Hyderabad)
🏢 HCLTech
📍 Hyderabad