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DevOps Engineer

DevOps Engineer

Wissen Infotechnadiad, gujarat, in
12 hours ago
Job description

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 systems
  • Expert-level proficiency with MLflow for experiment tracking, model registry, and deployment
  • Experience with agent frameworks (LangChain, AutoGen, CrewAI, or similar)
  • Knowledge of prompt engineering and LLM orchestration patterns
  • Understanding of agent memory systems and state management
  • Programming & Infrastructure :

  • Advanced Python programming with asyncio experience
  • Docker and Kubernetes for containerized agent deployment
  • Experience with message brokers (Redis, RabbitMQ, Apache Kafka)
  • RESTful API design and implementation
  • Microservices architecture patterns
  • Cloud & DevOps :

  • AWS / Azure / GCP cloud platforms with focus on serverless and container services
  • CI / 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 deployment
  • Experience with vector databases (Pinecone, Weaviate, Chroma)
  • Knowledge of RAG (Retrieval-Augmented Generation) systems
  • Data pipeline tools (Apache Airflow, Prefect)
  • Qualifications

  • Bachelor's / master's degree in computer science, Engineering, or related field
  • 2-5 years of experience with mandatory focus on agentic systems MLOps
  • Demonstrated experience with MLflow in production environments
  • Strong software engineering fundamentals and design patterns
  • Experience with distributed systems and scalability challenges
  • Understanding of AI safety and alignment considerations
  • Excellent problem-solving and debugging skills
  • What We Offer

  • Work on cutting-edge agentic AI systems for Fortune 500 clients
  • Opportunity to shape MLOps practices for next-generation AI systems
  • Competitive compensation with performance bonuses
  • Comprehensive health and wellness benefits
  • Flexible hybrid work arrangements
  • Dedicated learning budget for conferences and certifications
  • Note : Applications without demonstrated experience in agentic systems MLOps and MLflow will not be considered.

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