Python FSD with Angular at MNC · Mumbai · 7 - 9 years · ₹8L - ₹13L / yr · Posted 7 Oct 2026

Full Stack Developer – AI/ML & GenAI
Location: Mumbai
Experience: 7–9 Years
Employment Type: Full-time
Virtual Drive: Saturday
We are looking for a Python Full Stack Developer with 3+ years of hands-on experience in AI/ML and Generative AI.
Key Skills: Python Full Stack, FastAPI/Flask/Django, React/Angular, AI/ML, GenAI, LLMs, RAG, Embeddings, Vector Databases, Cloud (AWS/Azure/GCP), CI/CD, Docker & Kubernetes.

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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.
- 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.
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.
We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:
✅ Real-time self-coding based on tasks
✅ Autonomous multi-agent collaboration
✅ AI-powered decision-making
✅ Cross-platform compatibility (Desktop, Web, Mobile)
We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.
### Responsibilities:
- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)
- Integrate large language models (GPT-4o, Claude, open-source LLMs)
- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)
- Work on real-time task execution pipelines
- Build cross-platform apps using Electron or Flutter
- Implement Redis, Vector databases, scalable APIs
- Guide the architecture of autonomous, self-coding AI systems
### Must-Have Skills:
- Python (advanced, AI applications)
- AI/ML experience, including multi-agent orchestration
- LLM integration knowledge
- Full-stack development: React or Next.js
- Redis, Vector Databases (e.g., Pinecone, FAISS)
- Real-time applications (websockets, event-driven)
- Cloud deployment (AWS, GCP)
### Good to Have:
- Experience with code-generation AI models (Codex, GPT-4o coding abilities)
- Microservices and secure system design
- Knowledge of AI for workflow automation and productivity tools
Join us to work on cutting-edge AI technology that builds the future of autonomous software.
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 :
- Round 1 – GT Technical Interview : 60 minutes
- Round 2 – Client Technical Interview : 60 minutes
- Round 3 – Project Round : 60 minutes
- 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.
Python Full Stack GenAI Engineer
Experience: 5+ Years
Location: Bangalore / Hyderabad
Role Overview:
We are looking for a Python Full Stack GenAI Engineer with strong hands-on experience in Python development and Generative AI solutions.
Must-Have Skills:
- Python – Strong hands-on experience
- Generative AI / GenAI
- LLMs & Prompt Engineering
- LangChain / LangGraph
- RAG & Vector Databases
- REST APIs / FastAPI
- React.js / Frontend development
- SQL
- AI Agent / Agentic AI experience is a plus
Responsibilities:
- Develop scalable Python-based applications with GenAI capabilities
- Build LLM, RAG and AI Agent solutions
- Develop REST APIs using FastAPI
- Integrate AI services with full-stack applications
- Work with frontend technologies such as React.js
- Design and optimize production-ready GenAI solutions
Interested candidates can apply with their updated resume.
Strong AI Engineer / Machine Learning Engineer profiles.
2
Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
7
Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
9
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
10
Mandatory (Age) - Candidate's Age should be below 28 Years

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
- Python
- React.js
- Gen AI / Agentic AI
- RAG + LLM
- LangChain / LangGraph
- MongoDB
- Java + Spring Boot
- REST APIs / Microservices
- Vector Databases / Embeddings
- 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
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
Experience - 4 to 6 year
Location – Ahmedabad/Pune/Indore
- Additional Job Description
Additional Job Description
Required Skills and Experience:
- Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
- Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
- Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
- Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
- Demonstrated experience implementing content filtering / moderation systems.
- Solid skills working with structured and unstructured data and advanced feature engineering.
- Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
- Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
- Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
- Good knowledge of security, data governance, and privacy best practices for AI systems.








