Agentic AI Engineer (GenAI/ Python)

360 Technology; Pune District; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

360 Technology seeks an experienced Agentic AI Engineer to design and deploy autonomous AI agents for banking apps. You will build agentic workflows, integrate LLM-powered solutions with enterprise systems, and ensure secure, scalable production-grade AI applications.

The role requires hands-on Python, experience with agent orchestration frameworks, RAG pipelines, and compliance with financial services security and governance.

Qualifications

• Strong hands-on Python programming and enterprise software development.
• Experience building agentic AI applications, AI agents, and multi-step autonomous workflows.
• In-depth knowledge of LLMs, Generative AI, prompt engineering, function calling, and structured outputs.
• Familiarity with LangGraph, LangChain, or similar orchestration frameworks.
• Experience with RAG pipelines, embeddings, vector databases, and semantic search.
• Experience integrating AI solutions with REST APIs, databases, and enterprise systems.
• Understanding of evaluation, observability, testing, error handling, and performance optimization.
• Familiarity with cloud services (AWS/Azure/GC) and deployment platforms.
• Understanding of AI security, access controls, governance, and data privacy.

Responsibilities

• Design, develop, and deploy AI agents capable of reasoning, planning, tool execution, and multi-step orchestration.
• Build multi-agent systems and agentic workflows using LangGraph, LangChain, or AutoGen frameworks.
• Develop production-grade AI applications using Python, LLMs, prompt engineering, and structured outputs.
• Implement Retrieval-Augmented Generation using enterprise sources, vector databases, and embeddings.
• Integrate AI agents with REST APIs, enterprise apps, databases, and banking platforms.
• Implement tool calling, workflow orchestration, memory management, and human-in-the-loop approvals.
• Develop automated evaluation, monitoring, tracing, and testing frameworks for reliability.
• Apply guardrails to mitigate hallucinations, prompt injections, and data exposure risk.
• Ensure compliance with banking security, data privacy, auditability, and responsible AI standards.
• Collaborate with stakeholders, architects, data engineers, and dev teams to deliver banking AI solutions.
• Optimize agent performance, latency, scalability, and operational cost.

Skills

Python programming

Agentic AI

LLMs

Prompt engineering

LangGraph

LangChain

Tool integration

REST APIs

Vector databases

RAG pipelines

Cloud platforms

Security and governance

Tools

LangGraph

LangChain

Microsoft AutoGen

Job description

We are seeking an experienced Agentic AI Engineer with strong hands-on expertise in Python, Generative AI, Large Language Models (LLMs), and AI agent development to build intelligent, autonomous, and goal-oriented AI solutions for banking applications.

The ideal candidate will have experience designing and implementing agentic workflows, developing AI agents that can use tools and APIs, and integrating LLM-powered solutions with enterprise banking systems. Candidates must possess strong software engineering skills and the ability to build secure, scalable, and production-ready AI applications in a regulated financial services environment.

Key Responsibilities

• Design, develop, and deploy AI agents capable of reasoning, planning, tool execution, and multi-step task orchestration.
• Build multi-agent systems and agentic workflows using frameworks such as LangGraph, LangChain, or Microsoft AutoGen.
• Develop production-grade AI applications using Python, LLMs, prompt engineering, and structured output generation.
• Implement Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources, vector databases, and embedding models.
• Integrate AI agents with REST APIs, enterprise applications, databases, and banking platforms.
• Implement tool calling, workflow orchestration, memory management, and human-in-the-loop approval mechanisms.
• Develop automated evaluation, monitoring, tracing, and testing frameworks to ensure AI solution reliability.
• Apply guardrails to mitigate hallucinations, prompt injection, unauthorized tool usage, and inappropriate data exposure.
• Ensure compliance with banking security, data privacy, auditability, and responsible AI requirements.
• Collaborate with banking stakeholders, architects, data engineers, and application development teams to deliver business-focused AI solutions.
• Optimize agent performance, response accuracy, latency, scalability, and operational cost.

Required Technical Skills

• Strong hands-on programming experience in Python and enterprise software development.
• Practical experience developing Agentic AI applications, AI agents, and multi-step autonomous workflows.
• Strong knowledge of LLMs, Generative AI, prompt engineering, function calling, and structured outputs.
• Hands-on experience with LangGraph, LangChain, or equivalent agent orchestration frameworks.
• Experience implementing RAG pipelines, embeddings, vector databases, and semantic search.
• Experience integrating AI solutions with REST APIs, enterprise systems, and databases.
• Knowledge of agent evaluation, observability, testing, error handling, and performance optimization.
• Familiarity with cloud-based AI services and deployment platforms such as AWS, Azure, or Google Cloud.
• Understanding of AI security, access controls, responsible AI, and enterprise data governance.

Banking Domain Requirements

• Experience delivering AI, ML, or GenAI solutions within banking or financial services.
• Understanding of banking workflows such as customer service, payments, lending, fraud detection, risk management, compliance, or operations.
• Knowledge of sensitive financial data handling, regulatory controls, audit trails, and secure AI implementation.
• Ability to develop AI solutions that operate within controlled banking environments and comply with enterprise security standards.

Preferred Qualifications

• Experience with multi-agent orchestration, planning, state management, and agent-to-agent communication.
• Exposure to Model Context Protocol (MCP), enterprise tool integrations, and AI workflow automation.
• Experience with LLMOps, CI/CD, containerization, and production deployment of AI applications.
• Familiarity with AI governance, model evaluation, observability, and human approval workflows.
• Must be a hands-on Agentic AI Engineer, not a candidate with only theoretical GenAI knowledge.
• Must demonstrate practical experience building and implementing AI agents and orchestrated workflows.
• Strong Python coding skills and enterprise application development experience are mandatory.
• Banking or financial services experience is strongly preferred.
• Candidates must be comfortable working directly with onshore banking stakeholders and collaborating with distributed engineering teams.