Mandatory skills - Python, AI/LLM, LangGraph (preferred), LangChain

The AI Engineer will design, implement, and optimize AI agent workflows using LangGraph, Python, and up-to-date LLM ecosystems. This role involves designing autonomous reasoning systems, integrating tools and APIs, and creating scalable pipelines that power enterprise-grade AI applications. The ideal candidate has strong software engineering fundamentals, practical AI engineering experience, and a passion for building robust, production-ready agent solutions.

Responsibilities:
Design and implement agentic workflows using LangGraph, LangChain, or similar orchestration frameworks.
Develop LLM-powered agents with capabilities such as tool calling, state management, memory handling, and decision-based execution paths.
Build and maintain Python-based services, tools, and utilities supporting agent workflows.
Integrate external systems, APIs, vector databases, and enterprise data sources into agent pipelines.
Design, implement, and optimize RAG pipelines, embeddings workflows, and contextual reasoning flows.
Optimize agent performance, cost, and reliability; implement guardrails, validations, and structured output patterns.




Troubleshoot and resolve issues related to agent logic, model behavior, integrations, and workflow execution.
Document architecture, configurations, design decisions, and best practices for agent development.
Collaborate with architects, AI engineers, and cross-functional teams to deliver end-to-end AI capabilities.

Skill Set Required
6+ years of overall software development experience.
3+ years of Python development (OOP, async programming, API development; packaging, modularity, testing).
1+ year of hands-on AI/LLM engineering experience.
Experience building AI agents using LangGraph (preferred), LangChain, or similar state-graph/agent frameworks.
Strong understanding of prompt engineering, tool/function calling, state/graph workflow design, and structured output generation (JSON, Pydantic).
Experience with vector databases (FAISS, Pinecone, Weaviate, Chroma, etc.).
Proficiency integrating with OpenAI, Azure OpenAI, Anthropic, or other LLM providers.
Familiarity with CI/CD workflows, Git, and cloud deployment settings (Azure/AWS/GCP).
Robust debugging, problem-solving, and system design skills.

📌 Senior Ai Engineer Bengaluru
🏢 Quess
📍 Bengaluru