PYTHON + AI

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.

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: 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.

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.

Senior Generative AI Engineer

Employment Type: Permanent with VDart Digital

Work Location: Marathalli, Bengaluru

Job Description

We are seeking a highly skilled Senior Generative AI Engineer with strong expertise in designing, developing, and deploying enterprise-scale AI solutions using Large Language Models (LLMs) and modern Generative AI frameworks. The ideal candidate should have hands-on production experience building scalable GenAI applications, AI agents, autonomous workflows, and Retrieval-Augmented Generation (RAG) systems in cloud-native environments.

This role requires deep technical expertise in LLM orchestration, AI application architecture, prompt engineering, vector databases, MLOps, and production deployment of AI systems. Candidates should have proven experience delivering real-world AI solutions in enterprise environments with strong exposure to cloud platforms and DevOps practices.

Key Responsibilities

• Design, build, and deploy enterprise-grade Generative AI applications using Large Language Models (LLMs).
• Develop intelligent AI agents and autonomous workflows using frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar agentic AI frameworks.
• Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search technologies.
• Work extensively on prompt engineering, tool calling, memory management, agent orchestration, and multi-agent systems.
• Integrate and manage LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar foundation models.
• Develop scalable AI services and APIs using Python and FastAPI.
• Build production-ready AI solutions with high availability, scalability, monitoring, and observability.
• Deploy and manage AI applications in cloud-native environments using Docker and Kubernetes.
• Collaborate with Data Science, ML Engineering, and DevOps teams to operationalize AI solutions.
• Implement CI/CD pipelines and automated deployment processes for AI workloads.
• Monitor model performance, latency, reliability, and operational efficiency in production environments.
• Ensure AI solutions follow enterprise security, governance, and responsible AI standards.
• Evaluate and adopt emerging Generative AI tools, frameworks, and models.

Required Skills

Generative AI & LLM Expertise

• Strong hands-on experience with Generative AI and Large Language Models (LLMs).
• Production-level experience building and deploying GenAI applications.
• Expertise in LangChain, CrewAI, LangGraph, AutoGen, or similar frameworks.
• Experience with AI agents, autonomous workflows, and multi-agent architectures.
• Strong understanding of prompt engineering, embeddings, model evaluation, and LLM orchestration.
• Experience integrating OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar models.

RAG & Vector Databases

• Strong experience implementing RAG pipelines and semantic retrieval systems.
• Experience with vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
• Understanding of chunking strategies, embeddings, indexing, reranking, and retrieval optimization.

Python & AI Development

• Strong proficiency in Python.
• Experience with FastAPI for AI service and API development.
• Experience with AI/ML libraries and data processing tools such as Pandas and NumPy.

Cloud & Production Deployment

• Mandatory production experience on at least one cloud platform:
• Microsoft Azure
• Experience deploying scalable AI applications in enterprise production environments.
• Hands-on experience with Docker, Kubernetes, Jenkins, Terraform, and CI/CD pipelines.
• Strong understanding of MLOps, AI deployment lifecycle, monitoring, and observability.

Engineering & Operational Excellence

• Strong understanding of software engineering best practices.
• Experience with Git, version control, automated testing, and release management.
• Experience building secure, scalable, and high-performance AI solutions.
• Ability to troubleshoot production AI systems and optimize performance.

Preferred Skills

• Experience with AI observability and evaluation frameworks.
• Exposure to fine-tuning, PEFT, LoRA, or model optimization techniques.
• Experience with enterprise AI governance and responsible AI practices.
• Knowledge of distributed AI systems and scalable inference architectures.
• Familiarity with AI security and compliance standards.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3–8 years of overall software engineering experience.
• Minimum 3+ years of hands-on experience in Generative AI and LLM-based application development,
• Proven track record of delivering enterprise-scale AI solutions in production environments.
• Strong communication and stakeholder management skills.

Job Description:

We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.

Key Responsibilities:

• Develop and deploy GenAI and Agentic AI applications.
• Build RAG pipelines, LLM workflows, and AI agents.
• Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Implement tool calling, context retrieval, and LLM orchestration.
• Integrate AI solutions with APIs and cloud platforms.
• Work with AWS/Azure/GCP, Docker, and CI/CD.

Required Skills:

• Strong Python programming skills.
• 3+ years of GenAI/Agentic AI experience.
• RAG and LLM orchestration.
• LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
• MCP and A2A knowledge.
• Cloud, APIs, Docker, and CI/CD experience.

Preferred Experience:

Hands-on experience building and deploying production-ready AI solutions.

Senior Agentic AI Engineer - (Freelance)

Positions: 2

Experience: Ideally 4(J–(J8 years with strong software-engineering fundamentals and recent hands-on Agentic AI experience.

Mission

Build UC2's governed AI agents capable of reasoning across and interacting safely with enterprise IT systems.

Mandatory capabilities

• Python
• LangGraph
• Agentic AI
• Tool/function calling
• Stateful workflows
• Structured outputs
• Human-in-the-loop
• Guardrails
• Agent state/checkpointing
• Agent evaluation
• FastAPI
• REST APIs
• Async Python

Retry/timeout/error handling

Highly desirable

MCP, LangChain, Semantic Kernel, agent observability, event-driven architecture and experience integrating AI agents with ServiceNow/Splunk/Confluence or similar enterprise platforms.

The candidate should understand how to engineer:

Design and develop Agentic AI systems using LLMs, tools, memory,

workflows, and MCP.

Build production-grade RAG pipelines, including ingestion, chunking,

embeddings, retrieval, reranking, and evaluation.

Implement context engineering strategies for improving LLM accuracy,

relevance, and reliability.

Develop and integrate MCP-based tools and services for AI agents.

Work with LLMs, SLMs, quantized models, and model optimization

techniques for efficient inference.

Develop scalable backend services and APIs for AI applications.

Design databases and data models supporting AI/agentic applications.

Implement AI observability covering latency, token usage, cost, failures,

quality, and agent/tool execution.

Apply AI governance and responsible AI practices, including security,

access control, data privacy, and auditability.

Optimize AI systems for latency, scalability, cost, and reliability.

Collaborate with engineering and product teams to take AI solutions from

POC to production.

Strong hands-on experience with GenAI, LLMs, and Agentic AI.

Experience building RAG applications.

Strong understanding of Context Engineering and prompt/context

optimization.

Role Overview

We are looking for a hands-on AI/ML Engineer to design, develop, and deploy

production-ready GenAI and Agentic AI applications. The role involves building

intelligent agents, RAG pipelines, AI APIs, backend services, and scalable AI

infrastructure with a strong focus on context engineering, observability,

governance, and model optimisation.

Key Responsibilities

Required Skills

Practical experience with MCP (Model Context Protocol).

Experience with frameworks such as LangChain, LangGraph,

LlamaIndex, or equivalent.

Knowledge of LLM/SLM deployment and quantization techniques.

Strong Python backend development experience.

Experience developing REST APIs using FastAPI/Flask or equivalent.

Strong understanding of SQL/NoSQL databases and database design.

Experience with vector databases such as Qdrant, Pinecone, Weaviate,

ChromaDB, or FAISS.

Understanding of AI observability, evaluation, monitoring, and

governance.

Experience with cloud platforms and production deployment is preferred.

Strong understanding of software engineering principles, Git, testing, and

CI/CD.

Location: Pune / Gurgaon

Position: AI Engineer

work mode: WFO

  Job Description.

​

 Job responsibilities:

• Responsibility for design, implementation and deployment of Generative AI, Agentic frameworks at scale
• Strong in programming - Python a
• Previous experience of working on Computer Vision projects and VLM /VLAM models.
• In depth awareness of Transformer architectures and End to End Deep neural networks
• Full stack AI / ML development experience
• Design, build & maintain efficient and reliable Agentic / Generative AI code leveraging pipelines
• Hosting and deployment knowledge in GCP or AWS or Azure along with advanced engineering concepts to build user friendly UI interface for easy adoption.

    Requirements:

 ·      4 to 8 years overall years of experience (Agentic AI, Generative AI, VLM, VLAM and LLM) with significant exposure in Development, Architecture design, scaling and hosting in cloud.

    Must Have –

 ·      Architecting and solutioning experience with Python and FAST API, Agentic Ai frameworks, VLMs, VLAMs, Open source LLM’s and Code based LLM models at scale with - Langchain /      Ollama, embeddings, Memory      Management etc.,

·      Practical experience in implementing Explainable and ethical AI models  Practical experience in implementing frameworks like RAG/ CAG/ Self-reflective RAG etc.,

·      Experience in cloud hosting either AWS or Azure or GCP.

·      Experience in ML-OPS - Implement a feedback mechanism to continually improve the model over time through feedback loop and monitoring KPI’s in production.

·      Experience with Quantization and Kubernetes or docker

    Good to have

·      gRPC implementation to expose the API’s on a server for easy usage and good user interface

·      Streamlit front end creation

·      Experience with SAFe framework deliveries.

Role: AI Developer

Experience: 3–4 Years

Employment Type: Full-Time

Location: Goregaon, Mumbai

About the Role

We are looking for an experienced AI Developer with 3–4 years of software development experience and strong hands-on exposure to Generative AI, AI Agents, Copilots, and AI-powered application development.

The candidate will be responsible for building production-ready AI solutions, developing agentic workflows, modernizing legacy applications, and integrating LLM capabilities into enterprise applications.

Key Responsibilities

• Design, develop, and deploy AI Agents and agentic workflows for enterprise use cases.
• Build AI Copilots and LLM-powered applications using modern AI frameworks and APIs.
• Develop RAG-based applications using embeddings, vector databases, and enterprise data.
• Work on legacy application migration and modernization, leveraging AI-assisted development and code transformation techniques.
• Analyze legacy codebases and design strategies for AI-driven migration, refactoring, and modernization.
• Integrate LLMs with enterprise applications, APIs, databases, and third-party systems.
• Implement tool calling, function calling, multi-agent workflows, and workflow automation.
• Perform prompt engineering, context optimization, model evaluation, and AI application testing.
• Take ownership of AI solutions from POC and prototyping through production deployment.
• Collaborate with product managers, architects, and engineering teams to convert business requirements into scalable AI solutions.
• Stay updated with emerging technologies in Generative AI, Agentic AI, LLMs, and AI-assisted software development.

Required Skills

• 3–4 years of professional software development experience.
• Strong proficiency in Python and/or JavaScript/TypeScript.
• Hands-on experience developing Generative AI / LLM-based applications.
• Strong understanding of AI Agents, RAG, Prompt Engineering, LLM APIs, and embeddings.
• Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
• Experience working with REST APIs, databases, Git, and cloud environments.
• Hands-on experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent.
• Good understanding of software architecture, debugging, testing, and deployment practices.

Good to Have

• Experience with Microsoft Copilot / Copilot Studio.
• Experience working with Claude, OpenAI, Gemini, Azure OpenAI, or open-source LLMs.
• Experience in legacy application migration, modernization, or code conversion.
• Knowledge of Azure AI / AWS / Google Cloud AI services.
• Experience with MCP, multi-agent systems, tool calling, and AI orchestration.
• Experience building enterprise-grade AI solutions with focus on security, scalability, and performance.