Position Overview
We are seeking a specialized MLOps Engineer with mandatory experience in building and maintaining pipelines for evaluation and deployment of agentic systems . This role is critical to our growing AI / ML practice in Bengaluru, focusing on productionizing autonomous AI agents and multi-agent systems at enterprise scale.
Key Responsibilities
- Design and implement end-to-end MLOps pipelines specifically for agentic systems including autonomous agents, multi-agent frameworks, and LLM-based applications
- Build robust evaluation frameworks for agent performance, including metrics for task completion, decision quality, and agent collaboration
- Deploy and orchestrate agentic systems using containerization and microservices architectures
- Implement comprehensive monitoring for agent behavior, performance degradation, and system health
- Establish version control and experiment tracking for agent configurations, prompts, and model weights using MLflow (mandatory)
- Create automated testing pipelines for agent reasoning, tool usage, and edge case handling
- Build scalable infrastructure for agent deployment including API gateways, message queues, and state management
- Implement safety and guardrail mechanisms for production agent deployments
- Develop rollback and A / B testing strategies for agent updates and model changes
- Collaborate with ML researchers to productionize novel agent architectures
Required Technical Skills
MLOps & Agentic Systems (Mandatory) :
Proven experience building evaluation and deployment pipelines for agentic systemsExpert-level proficiency with MLflow for experiment tracking, model registry, and deploymentExperience with agent frameworks (LangChain, AutoGen, CrewAI, or similar)Knowledge of prompt engineering and LLM orchestration patternsUnderstanding of agent memory systems and state managementProgramming & Infrastructure :
Advanced Python programming with asyncio experienceDocker and Kubernetes for containerized agent deploymentExperience with message brokers (Redis, RabbitMQ, Apache Kafka)RESTful API design and implementationMicroservices architecture patternsCloud & DevOps :
AWS / Azure / GCP cloud platforms with focus on serverless and container servicesCI / CD pipelines (Jenkins, GitLab CI, GitHub Actions)Infrastructure as Code (Terraform, CloudFormation)Monitoring and observability tools (Prometheus, Grafana, OpenTelemetry)ML & Data :
Understanding of LLM fine-tuning and deploymentExperience with vector databases (Pinecone, Weaviate, Chroma)Knowledge of RAG (Retrieval-Augmented Generation) systemsData pipeline tools (Apache Airflow, Prefect)Qualifications
Bachelor's / master's degree in computer science, Engineering, or related field2-5 years of experience with mandatory focus on agentic systems MLOpsDemonstrated experience with MLflow in production environmentsStrong software engineering fundamentals and design patternsExperience with distributed systems and scalability challengesUnderstanding of AI safety and alignment considerationsExcellent problem-solving and debugging skillsWhat We Offer
Work on cutting-edge agentic AI systems for Fortune 500 clientsOpportunity to shape MLOps practices for next-generation AI systemsCompetitive compensation with performance bonusesComprehensive health and wellness benefitsFlexible hybrid work arrangementsDedicated learning budget for conferences and certificationsNote : Applications without demonstrated experience in agentic systems MLOps and MLflow will not be considered.