Senior AI/MLOps Engineer (Remote - India)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior AI/MLOps Engineer in India.

We are seeking a highly skilled Senior AI/MLOps Engineer to lead the deployment, operations, and optimization of agentic AI systems at enterprise scale. This role will focus on implementing and running autonomous multi-agent LLM solutions that drive mission-critical processes across complex AI-native infrastructures. You will collaborate with cross-functional teams to ensure reliability, observability, and compliance while mentoring and guiding AI and MLOps practices. The position offers the opportunity to work on cutting-edge AI frameworks, operationalize RAG pipelines, and influence the evolution of enterprise AI systems. The environment is fast-paced, innovative, and remote-friendly, with a strong emphasis on autonomy, governance, and performance.

Accountabilities:

·        Architect, deploy, and maintain multi-agent orchestration frameworks for autonomous LLM workflows (e.g., FastAgent, FastMCP, LangGraph, AutoGen, CrewAI).

·        Design and operationalize RAG workflows, vector stores, and knowledge-graph connectors.

·        Implement end-to-end observability and monitoring using Prometheus, Grafana, OpenTelemetry, and incident playbooks.

·        Enforce governance, security, and compliance for AI systems, including PII handling and prompt-audit trails.

·        Collaborate with data engineers, MLOps, and DevOps teams to integrate CI/CD pipelines for AI workloads.

·        Benchmark agent performance, optimize token usage, and continuously improve AI operations frameworks.

·        Mentor junior engineers and enable teams to adopt best practices in AI-native infrastructure.

·        5+ years of experience in production ML/LLM operations, including 2+ years with autonomous agent systems.

·        Hands-on experience with agentic AI frameworks such as FastAgent, FastMCP, LangGraph, AutoGen, or CrewAI.

·        Proficiency with Kubernetes, Docker, Terraform (or Pulumi), and GitOps workflows.

·        Proven track record implementing RAG pipelines using Pinecone, Elasticsearch, or similar tools.

·        Experience with observability tools including Prometheus, Grafana, and OpenTelemetry/Jaeger.

·        Strong collaboration, mentoring, and communication skills.

·        Bonus: open-source contributions, experience with vLLM/TensorRT-LLM, cloud certifications, or multi-modal agent workflows.