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

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. 

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.

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.

Job Title : Senior Consultant – Full Stack Developer with AI

Experience : 5+ Years

Open Positions : 1

Location : Remote

Working Hours : 11:00 AM to 08:00 PM IST

Engagement : 6 to 8 Months Contract-to-Hire (C2H), with potential conversion to client payroll

Expected Joining : By the last week of August / 1st week of September

Role Overview :

Thoughtworks is looking for a Senior Consultant – Full Stack Developer with AI experience who can design and develop scalable full-stack applications while leveraging modern AI development tools and agentic AI capabilities.

The ideal candidate should have strong hands-on experience with Python, JavaScript / React.js, AWS Bedrock Agent Core, Docker, Kubernetes, and modern AI-assisted development frameworks and tools. Experience building MCP servers / tools, AI skills, or integrations using tools such as Cursor, Claude Code, Codex, or GitHub Copilot will be highly valuable.

The candidate should be comfortable working across application development, AI integration, cloud technologies, and containerized environments.

Mandatory Skills :

Python, React.js / JavaScript, AWS Bedrock Agent Core, Docker, Kubernetes, MCP / AI Skills, Cursor / Claude Code / Codex / GitHub Copilot, Full-Stack Development.

Key Responsibilities :

• Design, develop, and maintain scalable full-stack applications using modern development practices.
• Build backend services and APIs using Python and related frameworks.
• Develop responsive and scalable frontend applications using ReactJS or other JavaScript frameworks.
• Design and implement AI-powered solutions using AWS Bedrock Agent Core.
• Build and integrate AI agents, tools, skills, and workflows into enterprise applications.
• Develop and work with MCP (Model Context Protocol) servers, tools, or integrations.
• Leverage AI-assisted development platforms and coding tools such as Cursor, Claude Code, Codex, or GitHub Copilot.
• Containerize applications and services using Docker.
• Deploy, manage, and troubleshoot containerized workloads using Kubernetes.
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable technical solutions.
• Follow engineering best practices around code quality, testing, security, performance, and maintainability.
• Contribute to CI/CD and cloud deployment processes; DevOps experience will be an added advantage.
• Participate in technical discussions, architecture decisions, code reviews, and project delivery.

Mandatory Skills :

• 5+ years of relevant software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS or another modern JavaScript framework.
• Hands-on experience with AWS Bedrock Agent Core.
• Strong experience with Docker.
• Hands-on experience with Kubernetes.
• Experience building MCP servers / tools, AI skills, or similar AI integrations.
• Experience using AI-assisted coding/development tools such as :
• Cursor
• Claude Code
• Codex
• GitHub Copilot
• Strong understanding of full-stack application development.
• Good understanding of API development, application architecture, and cloud-based solutions.

Nice to Have :

• Experience with DevOps practices and CI/CD pipelines.
• Experience with AWS cloud services beyond Bedrock.
• Experience with infrastructure automation and deployment.
• Experience building production-grade GenAI / Agentic AI applications.
• Experience with LLM integrations, AI agents, tools, and function calling.

Project Expectations :

Candidates should be able to explain at least one recent project in detail, including :

• Problem Statement : What business / technical problem were you solving ?
• Architecture & Approach : How did you design the solution ?
• Key Contributions : What did you personally build or own ?
• AI / Agent Implementation : How did you use AWS Bedrock Agent Core, MCP, or AI development tools ?
• Technology Stack : Python, React.js / JavaScript, AWS, Docker, Kubernetes, etc.
• Challenges : What were the major technical challenges ?
• Outcomes & Metrics : What measurable impact did the solution deliver, such as performance improvement, cost reduction, automation, productivity improvement, or reduced development time ?

Interview Process :

1. Round 1 – GT Technical Interview : 60 minutes
2. Round 2 – Client Technical Interview : 60 minutes
3. Round 3 – Project Round : 60 minutes
4. Additional Client Round : May be conducted on a case-by-case basis

Key Hiring Priorities :

Highest priority : Candidates with genuine hands-on experience in AWS Bedrock Agent Core + Python + React / JavaScript + Docker + Kubernetes + MCP / AI skills and practical experience using modern AI coding/agent development tools.

Note : Candidates should demonstrate hands-on implementation experience rather than only theoretical knowledge or exposure to the above technologies.

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.

Total Experience: 4+ years

Mode of Hire: Permanent

Required Skills Set (Mandatory): HTML, JavaScript, Node.js, Express.js, MongoDB, React/Next.js, AI Integration (LLMs/APIs - OpenAI, Anthropic, Gemini)

Desired Skills (Good if you have): Cloud Platforms (AWS), System Design, Application Security

What is the role all about?

We're hiring full-stack engineers who build with AI, not the traditional way. You should be fluent in modern web engineering, primarily Node.js, and just as fluent in using LLMs and AI tools (Cursor, Claude Code, and similar) to ship fast. Work that once took a month should take a week; what took a week should take a day.

The role spans a range, from architecting backends for non-trivial products like assistants and agents, to rapidly turning a requirement into a clean, customer-facing app or MVP. Be strong in at least one area, be comfortable across the system as a whole, and tell us where you're strongest so we can place you accordingly.

What will you do?

• Plan, build, and ship product features end-to-end, with AI embedded where it has the most impact.
• Integrate LLMs and AI APIs into production-grade applications.
• Use AI tools to prototype, build, and deliver at high speed without sacrificing quality.
• Design scalable APIs and data models with Node.js, Express.js, and MongoDB.
• Build responsive, performant, customer-facing interfaces with React/Next.js.
• Contribute to design discussions, code reviews, and architectural decisions.

What are we looking for?

AI leverage: 

• You've shipped real things using LLMs or AI APIs and instinctively reach for AI to move faster. 
• Comfortable with prompt engineering and judging AI output for production-readiness.

Engineering depth and delivery:

• Solid fundamentals: problem-solving, data structures, and how systems fit together. 
• At least 2+ years across frontend (React/Next.js), APIs (Node.js/Express.js), and databases (MongoDB). 
• You write clean, production-grade code and you ship.
• Knowledge of application security or ethical hacking is an advantage.

Culture

• Work with performance-oriented teams driven by ownership and passion.
• Learn to design systems for high accuracy, efficiency, and scalability.
• No strict deadlines, focus on delivering quality work.
• Meritocracy-driven, candid culture. No politics.
• Very high visibility regarding which startups and markets are exciting globally.

About Tracxn

Tracxn (Tracxn.com) is a Bangalore-based product company that provides a research and deal-sourcing platform for Venture Capital, Private Equity, Corp Dev, and professionals in the startup ecosystem.

We are a team of 800+ working professionals serving customers across the globe. Our clients include Funds such as Andreessen Horowitz, Matrix Partners, and GGV Capital, as well as Large Corporates such as Citi, Embraer & Ferrero.

Founders

• Neha Singh (ex-Sequoia, BCG | MBA - Stanford GSB)
• Abhishek Goyal (ex-Accel Partners, Amazon | BTech - IIT Kanpur)

About Technology Team

Tracxn's Technology team is 50+ members strong and growing. The technology team is subdivided into multiple smaller teams, each of which owns one or more services/components of the technology platform. Ours is a young team of motivated engineers with a minimal management structure, in which almost everyone is actively involved in technical development and design. We have a team-centric culture where ownership and responsibility for a feature or module lie with a team rather than an individual.

We work on an array of technologies, including but not limited to ReactJS, Next.js, Storybook, Webpack, Node, Mongo, AWS Lambda, Spring, Elastic Stack, MySQL, Kafka, Redis, Ansible, etc.

We value ownership, continuous learning, consistency, and discipline as a team.

Full-Stack Engineer (Backend Heavy)

Experience: 4–6 Years | Function: Engineering — Product | Location: On-site

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a Full-Stack Engineer with a strong backend bias to help build end-to-end product experiences across Lumen and Agent Studio. You will own features from database and API design through to the front-end experience, working closely with product and design to ship AI-powered experiences that real business users depend on every day.

What You’ll Do

Design and build backend services and APIs in Python that power core product and AI-agent features.

Build front-end interfaces and experiences that let users interact naturally with AI agents, insights and CRM workflows.

Own features end-to-end — from data modeling and backend logic to UI implementation, testing and release.

Work with product managers and designers to translate requirements into well-architected, scalable systems.

Integrate with LLM-based and agentic backend systems built by the AI/ML engineering team.

Optimize application performance, reliability and code quality across the stack.

Engage directly with customers and customer success teams to understand workflows, triage issues and inform roadmap decisions.

What We’re Looking For

4–6 years of professional full-stack engineering experience, with a clear backend-heavy skill set in Python.

Strong experience designing and building REST/GraphQL APIs, data models and scalable backend services.

Working proficiency with modern front-end frameworks (e.g., React) to build and integrate user-facing features.

Experience with relational/NoSQL databases, caching and cloud infrastructure.

Ability to move fast in a zero-to-one environment while maintaining code quality and system reliability.

Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

Experience building features on top of LLM or AI-agent backends.

Prior experience in CRM, SaaS or enterprise business applications.

Exposure to real-time or voice-based product interfaces.

• 6+ years of professional full-stack software engineering experience, with demonstrated ownership of production systems end-to-end (not just feature contribution within a large team).
• Backend: Strong proficiency in Python (FastAPI or Flask) — this is BuildTwin's primary backend language, used across the AI pipeline and application layer.
• Frontend: Strong proficiency in React and TypeScript, including building data-dense, interactive interfaces (dashboards, review workflows, file viewers) — not just CRUD forms.
• Database: Deep, hands-on experience with PostgreSQL — schema design, query optimization, indexing strategy, and multi-tenant data modeling.
• API design: Proven experience designing clean, versioned REST APIs, particularly ones serving as the integration layer between a backend/AI system and a frontend or third-party consumer.
• Cloud & DevOps: Production experience with AWS or Azure (compute, storage, queuing/messaging services), Docker, and CI/CD pipelines.
• Asynchronous & batch processing: Real experience with job queues (Celery, SQS, or equivalent) and designing systems that process work in parallel with proper failure isolation.
• Multi-tenant architecture: Direct experience building and securing systems that serve multiple isolated clients/tenants from shared infrastructure.

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

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