Walk-in || Gen AI Engineer

Note: Kindly attend the interview based on HR recruiter confirmation.

Job description

Key Responsibilities

• Deploy and manage LLM-based applications across cloud and hybrid environments.
  • 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.

Required Skills & Experience

• Strong 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.
  • Experience with CI/CD for ML or AI applications.
  • Programming and automation skills in Python or similar languages.
  • Familiarity with MLOps / LLMOps tooling, monitoring, and logging systems.