AI Engineer (Agentic Solutions & LangGraph) - Bangalore, India

Partners effectively with Data Scientists, Data Engineers, Analysts, Infrastructure Engineers, and peer AI Engineers to design, operationalize, integrate, and scale autonomous Agentic AI solutions and algorithmic products. Works autonomously with minimal guidance, demonstrating a proven track record in building production-grade multi-agent architectures, LLM-driven applications, and agentic workflows using LangGraph and LangChain.

Key Responsibilities

• Design & Deploy Agentic Systems: Build, test, and scale enterprise multi-agent workflows, stateful reasoning systems, and tool-augmented LLM architectures using LangGraph and LangChain.
  
• Operationalize & Scale: Develop, integrate, and optimize core algorithmic products and agent microservices into production environments.
  
• LLMOps & MLOps Infrastructure: Build and maintain CI/CD and LLMOps/MLOps pipelines, including automated evaluations (evals), monitoring, and testing for agent decision-making reliability.
  
• Cloud Deployment: Package, containerize, and deploy AI models and agentic workflows to cloud endpoints (Azure/GCP).
  
• Framework Development: Create internal accelerators, reusable agentic design patterns, and engineering frameworks to empower cross-functional project teams.
  
• Technical Ownership: Drive complex tasks independently with minimal supervision and collaborate closely with global engineering leadership.
  

Required Skills

• 4–7 years of hands-on experience in software, data, or AI engineering, with a primary focus on production AI and agentic systems.
  
• Deep Agentic AI Expertise: Hands-on proficiency with LangGraph (state graphs, persistence, human-in-the-loop workflows) and LangChain.
  
• Agent Architectures: Proven experience building multi-agent coordination systems, tool integration/function calling, memory management, and advanced RAG architectures.
  
• Core Development: Advanced proficiency in Python and building high-performance APIs with FastAPI or Flask.
  
• Software Engineering Standards: Mastery of software engineering best practices (GitHub, CI/CD pipelines, containerization, unit/integration testing, code reviews).
  
• Cloud & Orchestration: Cloud experience (Azure or GCP) and familiarity with workflow orchestration tools (Airflow, Kubeflow, or cloud-native orchestrators).
  
• Data & ML Foundations: Solid foundation in Python-based AI/ML libraries (PyTorch, TensorFlow, Scikit-learn), SQL/databases, and data platforms (Spark/Databricks).
  

Nice to Have

• Experience with additional agentic frameworks and vector ecosystems (e.g., AutoGen, CrewAI, LlamaIndex, Qdrant, Pinecone, pgvector).
  
• Experience with LLM evaluation frameworks (e.g., LangSmith, TruLens, Ragas).
  
• Cloud or AI/ML certifications (e.g., Google Professional ML Engineer, Azure AI Engineer Associate, AWS MLS-C01, Databricks ML Certification).
  
• Active open-source contributions to AI, LangChain/LangGraph, or data projects.
  
• Experience working in Agile/Scrum delivery setups for enterprise clients.
  

What We Offer

• Senior Expertise: Direct collaboration with a core team of senior ML/AI professionals (10+ years of experience each).
  
• Cutting-Edge Tech: Hands-on opportunity to build complex, production-grade Agentic and Generative AI platforms.
  
• Global Impact: Global project delivery for leading Fortune 500 companies.
  
• Culture: Dynamic, technology-agnostic environment that values technical autonomy and innovation.
  
• Growth: Competitive compensation package with the opportunity to shape AI strategy in our expanding India operations.
  

Location & Work Mode

• Location: Bangalore, Karnataka

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