Role: Senior Associate MLOps / LLMOps Engineer
Level: Senior Associate
Tower: AI Platform Engineering & MLOps (AI Managed Services)
Experience: 5–10 years
Key Skills: AWS Cloud & Infrastructure; MLOps & LLMOps; DevOps & CI/CD; Model & Artifact Versioning; Secure Deployments; Observability & Release Governance
Educational Qualification:
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or relevant cloud/DevOps certifications preferred)
Work Location: Bangalore and Hyderabad (based on your preference)
Job Description
As a Senior Associate – MLOps / LLMOps Engineer, you will design, build, and operate cloud-native AI and ML delivery pipelines that enable reliable, secure, and governed promotion of models and AI services from development to production. You will partner with AI engineers, data scientists, and operations teams to ensure models, prompts, and AI services are versioned, monitored, and deployed with confidence in an enterprise AWS setting.
This role is hands-on and execution-focused, emphasizing automation, reliability,
and controlled production releases for ML and LLM-based systems.
Key Responsibilities
AWS Cloud & Infrastructure Engineering
- Build and maintain AWS-based infrastructure supporting ML, LLM, and AI platforms.
- Use infrastructure-as-code principles to ensure repeatable and auditable environments.
- Configure IAM roles, networking, logging, and monitoring aligned to enterprise standards.
MLOps & LLMOps Enablement
- Implement MLOps and LLMOps patterns to support model training, packaging, deployment, and lifecycle management.
- Support deployment of traditional ML models as well as LLM-based services and workflows.
- Enable reproducibility across environments through standardized pipelines and artifacts.
CI/CD & DevOps Automation
- Design and maintain GitHub-based CI/CD pipelines for ML models, AI services, and infrastructure changes.
- Automate build, test, packaging, and deployment workflows.
- En
📌 MLops Engineer (Bengaluru)
🏢 PwC
📍 Bengaluru