Gen AI Engineer

Job Description

We are looking for an experienced Python Full Stack – GenAI / Agentic AI Engineer with 7+ years of experience in software development and strong hands-on expertise in Python backend development, React JS, Generative AI, and Agentic AI.

The ideal candidate should have experience building scalable backend services, modern web applications, and AI-powered applications using LLMs, RAG, agentic frameworks, and cloud platforms.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python.
• Develop robust REST APIs and microservices using FastAPI, Flask, or Django.
• Design API architecture, authentication mechanisms, error handling, and integrations.
• Develop responsive and interactive frontend applications using React JS.
• Work with React components, hooks, state management, and API integrations.
• Build and integrate Generative AI and Agentic AI applications using LLMs.
• Develop AI agents using frameworks such as LangChain and LangGraph.
• Implement RAG, embeddings, vector search, tool calling, memory, planning, and reasoning.
• Design and implement multi-agent systems and AI workflows.
• Apply prompt engineering techniques and appropriate guardrails for AI applications.
• Integrate AI applications with cloud-based AI platforms and services.
• Deploy applications using containers and cloud platforms.
• Work with CI/CD pipelines and application monitoring.
• Collaborate with cross-functional teams to design and deliver scalable solutions.

Required Skills

• 7+ years of overall software development experience.
• Strong hands-on experience in Python.
• Strong experience with FastAPI and REST API development.
• Experience with microservices architecture and API design.
• Hands-on experience with React JS.
• Strong experience in Generative AI / LLM applications.
• Hands-on experience in Agentic AI development.
• Experience with LangChain / LangGraph.
• Strong understanding of RAG, embeddings, vector search, and tool calling.
• Experience with multi-agent systems, memory, planning, and reasoning.
• Experience with at least one major cloud platform – AWS / Azure / GCP.
• Experience with containers, CI/CD, deployment, and monitoring.

Preferred Skills

• Google ADK
• Semantic Kernel
• Azure OpenAI
• Vertex AI
• AWS Bedrock
• Docker / Kubernetes
• AI application monitoring and observability
• Frontend testing and application performance optimization

Opportunity Details

Role: Python Full Stack – GenAI / Agentic AI Engineer

Experience: 7+ Years

Location: Hyderabad

Employment: Permanent Position

Work Mode: As per client requirement

Mandate Skills: Python, FastAPI, React JS, Agentic AI, LangChain/LangGraph, RAG, LLM, Cloud

Interview Focus Areas

Candidates should be prepared to demonstrate practical experience in:

• Python backend development
• FastAPI and REST APIs
• Microservices and API design
• React JS
• LLM / Generative AI applications
• Agentic AI architecture
• LangChain / LangGraph
• RAG and vector search
• Tool calling and multi-agent systems
• Cloud deployment and CI/CD

Position: Senior/Lead Full Stack Engineer – Gen AI / Agentic AI

Experience: 7+ Years

Employment: Permanent Position

Location: Banglore / Hyderabad

Job Summary

We are looking for a Senior/Lead Full Stack Engineer – Gen AI / Agentic AI with strong hands-on experience in Python, React.js, MongoDB, Java/Spring Boot and Generative AI/Agentic AI.

The candidate should have experience designing and developing scalable enterprise applications and implementing production-grade LLM, RAG, AI Agent and multi-agent solutions.

Key Responsibilities

• Design, develop and maintain scalable full-stack applications using Python, React.js, MongoDB and Java/Spring Boot.
• Build production-grade Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
• Develop RAG pipelines, AI agents, tool calling, memory management, planning and agent orchestration.
• Work with LangChain, LangGraph, MCP, vector databases and semantic search.
• Develop Python-based APIs, microservices and asynchronous applications using FastAPI/Flask/Django.
• Build REST APIs and event-driven microservices with focus on scalability, performance and resilience.
• Integrate LLMs, embeddings, vector stores and external enterprise tools/services.
• Implement prompt engineering, LLM evaluation, guardrails and AI observability.
• Develop responsive front-end applications using React.js.
• Work with MongoDB, SQL and hybrid data models.
• Implement CI/CD pipelines and support cloud/OCP deployments.
• Follow secure coding, testing, code quality and performance best practices.
• Participate in architecture, technical design, code reviews and mentoring of team members.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.

Mandatory Skills

1. Python
2. React.js
3. Gen AI / Agentic AI
4. RAG + LLM
5. LangChain / LangGraph
6. MongoDB
7. Java + Spring Boot
8. REST APIs / Microservices
9. Vector Databases / Embeddings
10. MCP / AI Agent orchestration

Good to Have

• FastAPI / Flask / Django
• Kafka / Solace
• Docker / Kubernetes
• AWS / Azure / GCP / OCP
• CI/CD – Jenkins / GitHub Actions
• LLMOps / AI evaluation / observability
• ELK / Grafana / Splunk / AppDynamics
• SQL / NoSQL
• Agile/Scrum

Python Full Stack Developer - AI/ML & GenAI (7-9 Years)

Role & Responsibilities

We are seeking an experienced Python Full Stack Developer with strong expertise in AI/ML, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-native application development.

• Design, develop, and maintain enterprise-grade full stack applications using Python (FastAPI, Flask, Django) and React/Angular.

• Build and deploy Generative AI solutions leveraging LLMs, AI Agents, Prompt Engineering, and RAG architectures.

• Develop scalable REST APIs, microservices, and backend services with a focus on performance, security, and reliability.

• Implement semantic search and knowledge retrieval solutions using embeddings, vector search, and vector databases such as Pinecone, Weaviate, ChromaDB, and FAISS.

• Integrate and optimize LLM-based solutions using OpenAI, Azure OpenAI, Claude, Gemini, and Llama.

• Develop and deploy AI/ML models using Machine Learning, Deep Learning, NLP, Transformers, and MLOps best practices.

• Design, implement, and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, and GitLab CI.

• Containerize and orchestrate applications using Docker and Kubernetes.

• Deploy and manage applications on Azure, AWS, or GCP.

• Collaborate with product owners, architects, data scientists, and engineering teams.

• Ensure application quality through code reviews, testing, monitoring, observability, and security standards.

• Contribute to AI governance, model evaluation, Responsible AI practices, and continuous improvement initiatives.

Mandatory Experience:

• 7-9 years of software development experience.

• 3+ years of hands-on experience in AI/ML and Generative AI.

• Strong expertise in Python Full Stack Development, LLMs, RAG, Embeddings, Vector Databases, Cloud Platforms, and CI/CD automation.

Job Title

Python Full Stack Developer – AI

Experience: 6-9 Years

Location: Bangalore (Hybrid)

Employment Type: Full-Time

Job Summary

We are seeking a highly skilled Python Full Stack Developer with AI expertise to design, develop, and deploy scalable AI-powered applications. The ideal candidate should have strong experience in Python, Full Stack Development, REST APIs, modern frontend frameworks, and Generative AI technologies, including LLMs, prompt engineering, and AI integrations.

The role involves building end-to-end web applications, integrating AI models, and collaborating with cross-functional teams to deliver innovative AI-driven solutions.

Key Responsibilities

· Design, develop, and maintain scalable full-stack applications using Python.

· Build responsive and interactive user interfaces using React.js, Angular, or Vue.js.

· Develop backend services and RESTful APIs using Django, Flask, or FastAPI.

· Integrate Generative AI models such as OpenAI GPT, Claude, Gemini, or Llama into business applications.

· Develop AI-powered chatbots, assistants, document processing, and workflow automation solutions.

· Implement prompt engineering techniques to optimize AI model performance.

· Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.

· Work with LangChain, LangGraph, or LlamaIndex for LLM orchestration.

· Integrate AI APIs and third-party services into enterprise applications.

· Design and optimize SQL and NoSQL databases.

· Deploy applications on AWS, Azure, or GCP.

· Develop CI/CD pipelines and manage deployments using Docker and Kubernetes.

· Write clean, reusable, and well-documented code following best practices.

· Participate in Agile ceremonies, code reviews, and sprint planning.

Required Technical Skills

Backend

· Python

· Django

· Flask

· FastAPI

Frontend

· React.js / Angular / Vue.js

· HTML5

· CSS3

· JavaScript (ES6+)

· TypeScript

AI / Generative AI

· OpenAI API

· Azure OpenAI

· Gemini API

· Claude API

· Llama Models

· LangChain

Databases

· PostgreSQL

· MySQL

· MongoDB

· Redis

Cloud & DevOps

· AWS / Azure / Google Cloud Platform

· Docker

· Kubernetes

· Git

· GitHub

· Jenkins

· CI/CD

API Development

· REST APIs

· GraphQL (Preferred)

· API Integration

Preferred Skills

· Machine Learning fundamentals

· NLP (Natural Language Processing)

· Hugging Face Transformers

· TensorFlow or PyTorch

· Kafka or RabbitMQ

· Elasticsearch

· Microservices Architecture

· Authentication (OAuth2, JWT)

Qualifications

· Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

· 6–9 years of experience in Python Full Stack Development.

· Hands-on experience with Generative AI and LLM-based application development.

· Experience working in Agile/Scrum environments. 

Senior Gen AI Full Stack Engineer:

• Strong background in AI/ML and Gen AI with a deep understanding of LLMs, NLP pipelines, and AI model lifecycle.

• Experience in designing and building guardrail systems for Gen AI applications – including prompt filtering, semantic validation, toxicity detection, and hallucination mitigation.

• Fast API experience for API development.

• Proficiency in Python with frameworks like LangChain, Transformers, OpenAI, and LLM orchestration tools.

• Strong DevOps skills including CI/CD, Docker, Kubernetes, and Git.

Experience integrating Gen AI models into enterprise platforms securely and ethically.

Role: Full Stack GEN AI Engineer

Location: Remote - Bengaluru

Duration: Fulltime With VDart Digital

The role demands a developer who is not just familiar with Large Language Models (LLMs), but is an expert in building autonomous agentic workflows using the modern GenAI stack (LangChain, CrewAI, Vector DBs). Expertise in system design, cloud-native technologies, and CI/CD for AI-driven applications is essential for this high-impact delivery role.

Responsibilities

· Design, develop, and maintain full-stack applications that are scalable, robust, and meet the company's quality standards, with a specific focus on Generative AI integration.

· Agentic Orchestration: Build and deploy sophisticated multi-agent systems and autonomous workflows using frameworks like LangChain, CrewAI, or LangGraph.

· Collaborate effectively with cross-functional teams to define, design, and ship new features that bridge the gap between raw AI power and intuitive user workflows.

· Exhibit strong problem-solving skills with an emphasis on product development and driving architecture choices that enable a world-class user experience.

· Utilize a variety of modern web technologies and frameworks (React.js, Angular, or Vue.js) to build responsive and accessible user interfaces.

· Develop and maintain RESTful APIs and services with optimal performance and scalability, handling streaming AI responses and complex function-calling logic.

· Ensure code quality, organization, and automatization through best practices, including unit tests for prompts, model evaluation pipelines, and automated CI/CD for AI-driven features.

· Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using Vector Databases and advanced retrieval techniques.

· Adapt to emerging technologies and frameworks, specifically new GenAI tools and frontier models, and apply them to operational and business needs.

· Manage individual project priorities, deadlines, and deliverables with minimal supervision.

Skill Requirements

· Excellent oral and written communication skills, with the ability to articulate complex AI and technical ideas to both technical and non-technical audiences.

· Profound knowledge of application development, data structures, networking, operating systems, and DBMS.

· Strong proficiency in backend programming languages for API development such as Python, Java, JavaScript (Node.js), or Go.

· Expertise in front-end technologies and frameworks such as React.js, Angular, or Vue.js.

· GenAI & Agentic Tools: Deep hands-on experience with LangChain, CrewAI, or AutoGen. Ability to manage agent memory, state, and tool-calling.

· In-depth understanding of SQL/NoSQL databases, data modeling, and experience with Vector Databases for RAG implementations.

· Solid grasp of system design, microservices architecture, and cloud-native technologies including Docker, Kubernetes, and GitHub Actions.

· Experience with distributed computing, machine learning frameworks, and tools, with a primary focus on Generative AI.

· Desirable (Good to Have): Experience with Generative or Adaptive UI development, where the interface dynamically adapts or renders components based on LLM outputs and real-time AI reasoning.

· A strong desire to learn and master new technologies and techniques in the rapidly evolving GenAI landscape.

Qualifications

· Bachelor’s degree in Computer Science, Engineering, or a related field.

· A minimum of 3-5 years of experience in full-stack development, with a proven track record of building and deploying Generative AI applications and agents.

· Portfolio of successfully deployed web applications and services, specifically showcasing AI agents, RAG implementations, or complex AI-driven features.

Key Responsibilities

• Design, develop, and maintain scalable Python backend applications for enterprise use cases.
• Develop robust REST APIs and microservices using Python frameworks such as FastAPI, Flask, or Django.
• Design and implement scalable backend services with proper API integration, authentication, error handling, logging, and monitoring.
• Develop responsive and scalable React.js frontend applications.
• Implement React Hooks, state management, API integration, reusable components, and frontend development.
• Integrate React.js applications with Python backend APIs and microservices.
• Design and develop Generative AI and LLM-powered applications.
• Build and integrate Agentic AI / AI Agent solutions for enterprise use cases.
• Develop RAG (Retrieval-Augmented Generation) pipelines using enterprise data and knowledge sources.
• Work with embeddings, vector databases, and vector search for semantic retrieval and knowledge-based applications.
• Develop AI agent workflows using frameworks such as LangChain, LangGraph, Google ADK, or Semantic Kernel.
• Implement tool calling and function calling to enable AI agents to interact with APIs, databases, enterprise systems, and external services.
• Apply prompt engineering techniques to improve LLM response quality, accuracy, consistency, and reliability.
• Integrate LLMs and GenAI capabilities into full-stack applications.
• Develop multi-step AI workflows, agent orchestration, and intelligent automation solutions.
• Design APIs and services for seamless integration between AI components, backend services, databases, and frontend applications.
• Work with cloud platforms such as AWS, Azure, or GCP for application and AI solution deployment.
• Develop production-ready applications with focus on scalability, performance, security, reliability, and maintainability.
• Troubleshoot and optimize backend, frontend, API, RAG, LLM, and Agentic AI components.
• Collaborate with architects, software engineers, AI/ML engineers, product teams, and business stakeholders.
• Participate in code reviews, technical discussions, testing, deployment, and production support.

Mandatory Skills

• Python Backend Development
• REST API / Microservices
• FastAPI / Flask / Django
• React.js
• React Hooks / State Management
• Frontend Development & API Integration
• GenAI / LLM
• Agentic AI
• RAG
• Embeddings / Vector Search
• LangChain / LangGraph / Google ADK / Semantic Kernel
• Prompt Engineering
• Tool Calling / Function Calling
• Cloud – AWS / Azure / GCP

Preferred Candidate Profile

• 8.5+ years of overall software development experience.
• Strong hands-on experience in Python backend development and API/microservices development.
• Strong experience in React.js and full-stack application development.
• Practical experience building GenAI/LLM applications.
• Hands-on experience with Agentic AI and AI agent frameworks.
• Good understanding of RAG, embeddings, vector search, and LLM-based application architecture.
• Experience with LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent agent frameworks.
• Strong understanding of prompt engineering and tool/function calling.
• Experience integrating AI capabilities with APIs, databases, enterprise applications, and external systems.
• Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
• Strong problem-solving, debugging, communication, and collaboration skills.
• Candidates should be available for immediate / short-term joining.

About the Role

We are looking for a hands-on Applied AI / Full Stack Engineer to build AI-powered products and experiences. The ideal candidate should be comfortable working across AI, backend, and frontend and taking features from idea to production.

Key Responsibilities

• Build and deploy AI/LLM-powered applications and features.
• Develop AI agents, RAG pipelines, tool/function-calling workflows and integrations.
• Build scalable backend APIs and services.
• Develop frontend applications using React/Next.js.
• Integrate LLMs such as OpenAI, Claude, Gemini, etc.
• Work with databases, cloud platforms and production deployments.
• Collaborate with product and design teams and take ownership of features end-to-end.

Must-Have Skills

• 3–6 years of software engineering experience.
• Strong Python and/or TypeScript/Node.js.
• Strong React.js / Next.js / TypeScript experience.
• Hands-on experience with LLMs / Generative AI.
• Experience with RAG, AI Agents or tool/function calling.
• Experience building and deploying real-world products.
• Good understanding of APIs, databases and cloud deployment.

Good to Have

• LangChain / LangGraph / LlamaIndex
• PostgreSQL / Vector Databases
• AWS / GCP / Azure / Vercel
• Docker / CI/CD
• Experience in an early-stage startup or AI product company.

We are looking for builders who can take a problem, experiment, build, ship and improve it—not just candidates with AI keywords on their resume.

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.

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.