Python Agentic AI at VY SYSTEMS PRIVATE LIMITED · Bengaluru (Bangalore) · 4 - 6 years · ₹1L - ₹17L / yr · Profitable · Posted 9 Oct 2026

Job Description:
We are looking for a skilled Python + Agentic AI Developer with hands-on experience in Python programming, Generative AI, and AI agent development. The candidate should have knowledge of building AI-powered applications, integrating Large Language Models (LLMs), and developing intelligent solutions using AI frameworks.
Primary & Mandatory Skills:
- Python Programming
- Agentic AI / AI Agents
- Generative AI (GenAI)
- Large Language Models (LLMs)
- AI-powered Application Development
Good to Have:
- LangChain / LangGraph
- RAG (Retrieval-Augmented Generation)
- FastAPI / REST APIs
- Prompt Engineering
Experience: 4 Years
Location: Bangalore (BGL)

About VY SYSTEMS PRIVATE LIMITED
About
Vy Systems is a Global Technology consulting, Solutions, and Managed Technology Services company. We service our customers with ‘RESPONSIVENESS’ as a key factor and we believe that timely response to any transaction increases the operational efficiency and accelerates the revenue and profitability to our customers.
The Company is founded and managed by a team of professionals having more than two+ decades of global experience in the business of Technology Consulting and Services.
Tech stack
Similar jobs (10)
Role Overview
We are looking for a Python Developer with strong experience in Generative AI and LLM-based applications. The candidate should have hands-on experience building AI solutions using Python, RAG, LangChain/LangGraph, and related GenAI technologies.
Mandatory Skills
Python, GenAI/LLM, RAG, LangChain/LangGraph, Agentic AI, FastAPI, REST API, Vector Database, Prompt Engineering, Microservices
Key Responsibilities
- Develop and maintain applications using Python and modern frameworks.
- Build GenAI/LLM-based applications and solutions.
- Develop RAG pipelines using vector databases.
- Work with LangChain/LangGraph for LLM and agent-based applications.
- Develop and integrate REST APIs using FastAPI.
- Implement Agentic AI workflows and AI-powered features.
- Integrate LLMs with existing applications and microservices.
- Apply prompt engineering techniques to improve AI application performance.
Role: Python + Agentic AI Engineer
We are looking for an experienced Python + Agentic AI Engineer with strong expertise in developing AI-powered applications and autonomous agent-based solutions.
Key Skills / Requirements:
• Strong hands-on experience in Python
• Experience with Agentic AI / AI Agents
• Hands-on with LangChain / LangGraph or similar agent frameworks
• Experience with Generative AI and LLMs
• Strong understanding of RAG (Retrieval-Augmented Generation) and Vector Databases
• Experience developing REST APIs using FastAPI
• Knowledge of Multi-Agent Systems, Tool/Function Calling and Agent Workflows
• Experience integrating LLMs with enterprise applications/APIs
• Exposure to cloud-based AI services is an advantage
Preferred Profile: Python Developer / AI Engineer / Generative AI Engineer / Agentic AI Engineer with hands-on experience building production-ready AI solutions.
Python (Gen AI or Agentic AI) - Hyderabad
7 + years of exp with more than 2 + years on Gen AI/Agentic AI.
Design and implement Generative AI and Agentic AI capabilities using LLM platforms and frameworks such as LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent.
Implement tool calling, RAG, memory, planning, reasoning, multi-agent orchestration, structured outputs, and human approval controls.
Integrate applications with REST APIs, relational and NoSQL databases, vector stores, message queues, and enterprise systems.
Role Overview
We are looking for a skilled Python Full Stack / Agentic AI Engineer to design, develop, and deploy AI-powered applications and intelligent agentic workflows. The ideal candidate should have strong expertise in Python, FastAPI, LLMs, RAG, LangChain/LangGraph, and modern full-stack development.
You will work on building scalable backend services, integrating Large Language Models, developing AI agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and creating production-ready AI applications.
Key Responsibilities
- Design and develop scalable backend applications using Python and FastAPI.
- Build and deploy Agentic AI solutions using LLMs and agent frameworks.
- Develop multi-step and multi-agent workflows using LangChain and LangGraph.
- Design and implement RAG (Retrieval-Augmented Generation) pipelines.
- Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
- Develop prompt engineering strategies and structured LLM workflows.
- Work with vector databases and embedding models for semantic search and knowledge retrieval.
- Build APIs and microservices for AI-powered applications.
- Integrate AI services with databases, third-party APIs, and enterprise systems.
- Develop conversation memory, tool calling, function calling, and agent orchestration capabilities.
- Implement evaluation, monitoring, logging, guardrails, and error handling for AI applications.
- Optimize applications for performance, scalability, reliability, and cost.
- Collaborate with product managers, frontend developers, data engineers, and other stakeholders.
- Write clean, maintainable, well-tested, and production-ready code.
- Participate in architecture discussions, code reviews, testing, and deployment activities.
Required Skills
Programming & Backend
- Strong proficiency in Python.
- Hands-on experience with FastAPI, REST APIs, and backend development.
- Strong understanding of asynchronous programming, API design, authentication, and middleware.
- Experience with SQL/NoSQL databases.
Generative AI / Agentic AI
- Strong understanding of LLMs and Generative AI.
- Hands-on experience building AI Agents / Agentic AI applications.
- Experience with LangChain and/or LangGraph.
- Knowledge of agent orchestration, tool calling, function calling, memory, and workflow management.
- Strong understanding of prompt engineering.
RAG
- Experience designing and implementing RAG architectures.
- Knowledge of document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
- Experience with vector databases such as FAISS, Chroma, Pinecone, Weaviate, Qdrant, or similar.
LLM & AI Integration
- Experience integrating commercial or open-source LLMs.
- Understanding of embeddings, context windows, temperature, token usage, and model selection.
- Experience with structured outputs and LLM-based workflows.
- Familiarity with LLM evaluation and observability is a plus.
Full Stack
- Working knowledge of HTML, CSS, JavaScript/TypeScript.
- Experience with React.js or similar frontend frameworks is preferred.
- Ability to integrate frontend applications with Python/FastAPI services.
Job Title: Python + GenAI Developer
Experience: 4–6 Years
Location: Bangalore / Hyderabad (as applicable)
Job Description:
We are looking for a skilled Python + Generative AI Developer with hands-on experience in Python development, LLM integration, and building AI-powered applications.
Key Responsibilities:
- Develop backend applications and REST APIs using Python.
- Build and integrate Generative AI solutions using LLMs.
- Work with frameworks such as LangChain or LangGraph.
- Implement Retrieval-Augmented Generation (RAG) pipelines and vector databases.
- Integrate OpenAI or other LLM APIs into applications.
- Collaborate with teams to develop, test, and deploy AI-powered solutions.
- Work with cloud platforms such as AWS, Azure, or GCP.
Required Skills:
- 4–6 years of Python development experience.
- Hands-on experience with Generative AI and LLMs.
- Experience with LangChain or LangGraph.
- Knowledge of RAG and vector databases.
- Experience developing REST APIs using FastAPI or Flask.
- Understanding of prompt engineering and LLM integration.
- Familiarity with Git and cloud platforms.
Preferred Skills:
- Experience with Agentic AI and AI agents.
- Knowledge of embeddings and semantic search.
- Experience with Docker and CI/CD.
🚀 Hiring: Python GenAI / Agentic AI Engineer
📍 Location: Hyderabad
💼 Experience: 7+ Years
🤖 GenAI / Agentic AI: 2+ Years
Mandatory Skills:
• Strong Python development experience
• Generative AI / Agentic AI
• LLMs & Prompt Engineering
• LangChain / LangGraph
• RAG & Vector Databases
• AI Agents / Multi-Agent Systems
• FastAPI / REST APIs
• LLM Integration
• Microservices & API Architecture
• Git & CI/CD
Looking for candidates with strong hands-on experience in building GenAI/Agentic AI solutions using Python, LLMs, RAG, and AI Agent frameworks.
Support with design and build to prove out agentic AI solution flow by working with other data
scientists and engineers to build, train Large Language Model (LLM) architectures, RAG
systems, and autonomous agentic workflows
Key qualifications:
>> AI solution design & Development: Design Agentic AI solutions using RAG (Retrieval-
Augmented Generation) and orchestration frameworks like LangGraph or LangChain.
>> Model Fine-Tuning: Solid understanding and experience with Pre-train, fine-tune, and
optimize open-source like BERT, LLama, and other proprietary foundation models for domain-
specific tasks
>> Solid Stats and ML foundations and (vibe) coding skills with Python, PySpark
>> Implement validation frameworks and tracing practices (using tools like Arize) to monitor
agent behavior, guard against model drift, and ensure compliance
>> Collaborate with Engineering to deploy models securely on cloud and on-prem ecosystems
We are currently hiring for the position of Python – GenAI / Agentic AI Engineer for one of our esteemed clients.
Please find the opportunity details below:
Position: Python – GenAI / Agentic AI Engineer
Location: Hyderabad
Experience: 7+ Years
GenAI / Agentic AI Experience: 2+ Years
Work Mode: Hybrid
Job Description
We are looking for an experienced Python professional with strong hands-on expertise in Generative AI / Agentic AI and LLM-based application development.
Core Mandatory Skills
- Python
- Generative AI / GenAI
- Agentic AI
- LLM
- LangChain / LangGraph
- Google ADK / Semantic Kernel / Equivalent Agent Frameworks
- RAG
- Tool Calling
- Memory, Planning & Reasoning
- Multi-Agent Orchestration
- Structured Outputs
- Human-in-the-Loop / Human Approval Controls
- REST APIs
- Relational & NoSQL Databases
- Vector Stores / Vector Databases
- Message Queues
- Enterprise System Integration
Key Responsibilities
- Design and implement Generative AI and Agentic AI capabilities using LLM platforms and frameworks.
- Build AI agents using LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent frameworks.
- Implement tool calling, RAG, memory, planning, reasoning, and multi-agent orchestration.
- Develop structured AI workflows with human approval controls.
- Integrate AI applications with REST APIs, databases, vector stores, message queues, and enterprise systems.
- Develop scalable and production-ready Python-based AI applications.
We are currently hiring for the position of Python – GenAI / Agentic AI Engineer for one of our esteemed clients.
Please find the opportunity details below:
Position: Python – GenAI / Agentic AI Engineer
Location: Hyderabad
Experience: 7+ Years
GenAI / Agentic AI Experience: 2+ Years
Work Mode: Hybrid
Job Description
We are looking for an experienced Python professional with strong hands-on expertise in Generative AI / Agentic AI and LLM-based application development.
Core Mandatory Skills
- Python
- Generative AI / GenAI
- Agentic AI
- LLM
- LangChain / LangGraph
- Google ADK / Semantic Kernel / Equivalent Agent Frameworks
- RAG
- Tool Calling
- Memory, Planning & Reasoning
- Multi-Agent Orchestration
- Structured Outputs
- Human-in-the-Loop / Human Approval Controls
- REST APIs
- Relational & NoSQL Databases
- Vector Stores / Vector Databases
- Message Queues
- Enterprise System Integration
Key Responsibilities
- Design and implement Generative AI and Agentic AI capabilities using LLM platforms and frameworks.
- Build AI agents using LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent frameworks.
- Implement tool calling, RAG, memory, planning, reasoning, and multi-agent orchestration.
- Develop structured AI workflows with human approval controls.
- Integrate AI applications with REST APIs, databases, vector stores, message queues, and enterprise systems.
- Develop scalable and production-ready Python-based AI applications.
Role Overview
We are looking for an experienced AI/ML Engineer with strong expertise in Python, Generative AI, LLMs, LangChain, and LangGraph. The candidate will be responsible for designing and developing AI-powered applications, intelligent agents, and scalable LLM-based solutions.
Key Responsibilities
- Design and develop AI/ML and Generative AI applications using Python and modern LLM technologies.
- Build LLM-based applications and AI agents using LangChain and LangGraph.
- Develop agentic workflows involving tool calling, memory, reasoning, and multi-step orchestration.
- Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or other foundation models.
- Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases.
- Work with embeddings, prompt engineering, semantic search, and document processing.
- Develop scalable APIs and backend services using Python, FastAPI, or Flask.
- Build and integrate AI solutions with existing applications and enterprise systems.
- Deploy and maintain AI/ML solutions on cloud platforms.
- Collaborate with data scientists, software engineers, and product teams to develop business-focused AI solutions.
Required Skills
- Strong hands-on experience in Python programming.
- Strong experience in AI/ML and Generative AI.
- Hands-on experience with LLMs and LLM-based application development.
- Strong experience with LangChain and/or LangGraph.
- Experience building AI Agents / Agentic AI workflows.
- Strong understanding of RAG, embeddings, vector databases, and prompt engineering.
- Experience with vector databases such as FAISS, Pinecone, Chroma, Weaviate, or Azure AI Search.
- Experience developing REST APIs using FastAPI/Flask.
- Good understanding of Machine Learning, NLP, and deep learning concepts.
- Experience with Azure / AWS / GCP cloud platforms.
Good to Have
- Experience with multi-agent systems and agent orchestration.
- Knowledge of MLOps / LLMOps.
- Experience with Docker, Kubernetes, and CI/CD.
- Knowledge of LLM evaluation, monitoring, observability, and AI governance.
- Experience with Azure OpenAI, Azure AI Foundry, or AWS Bedrock.







