AI-Full Stack Developer at NeoGenCode Technologies Pvt Ltd · Remote only · 5 - 7 years · ₹10L - ₹25L / yr · Raised funding · Remote only · Posted 31 Mar 2026

Overview:
We're looking for a Full Stack Developer with strong backend expertise who can build,
manage, and scale AI-driven products end to end. You'll play a critical role in designing
scalable architectures, optimizing performance and cost, and building robust AI and agentic
systems.
Responsibilities
1. Architect and build scalable backend systems using FastAPI, PostgreSQL, and Redis.
2. Design, develop, and maintain AI-driven applications, integrating multiple LLMs, APIs,
and agentic frameworks.
3. Implement vector databases (pgvector, Qdrant, etc.) for RAG and AI memory systems.
4. Orchestrate multi-agent AI systems with LangChain/LangGraph, including function
calling, agent collaboration, and monitoring.
5. Build and integrate RESTful APIs for frontend and external use.
6. Manage DevOps workflows, including CI/CD, cloud deployments (AWS/GCP), server
scaling, and logging/monitoring (Sentry).
7. Optimize application cost, latency, and reliability, balancing speed with LLM call
efficiency and caching strategies.
8. Collaborate with product, design, and AI teams to translate business requirements into
high-performing tech.
9. Maintain documentation and ensure code quality with tests, reviews, and async-first
architecture.
10. Contribute to frontend development (React + TypeScript) when necessary, ensuring
seamless API integration and data visualization.
Requirements
Core Skills
• Strong proficiency in Python and FastAPI.
• Experience with PostgreSQL (including pgvector) and SQLAlchemy (async).
• Solid understanding of Redis, RQ (Redis Queue), and caching mechanisms.
• Proven experience integrating LLMs and AI APIs (OpenAI, Anthropic, etc.).
• Hands-on experience with LangChain / LangGraph, RAG pipelines, and agent
orchestration.
• Experience working with cloud platforms (AWS / GCP) and managing file storage (S3).
• Familiarity with frontend stacks (React, TypeScript, Tailwind, Zustand).
• Working knowledge of DevOps: Docker, CI/CD pipelines, deployment automation, and
observability tools (Sentry, Mixpanel, Clarity).
Bonus / Nice to Have
• Experience building agent monitoring dashboards or AI workflows.
• Prior experience in startup or product-based environments.
• Understanding of LLM cost optimization, token management, and function calling
orchestration.
• Familiarity with external API integrations like BrightData, Hunter.io, Adzuna, and Serper.
• Experience building scalable AI products (e.g., chatbots, AI copilots, data agents, or
automation tools).
Mindset
• Startup-ready: comfortable working in fast-paced, ambiguous environments.
• Deep curiosity about AI systems and automation.
• Strong sense of ownership and accountability for shipped products.
• Pragmatic and cost-conscious in architectural decisions.
• Excellent communication and documentation skills.

About NeoGenCode Technologies Pvt Ltd
About
Welcome to Neogencode Technologies, an IT services and consulting firm that provides innovative solutions to help businesses achieve their goals. Our team of experienced professionals is committed to providing tailored services to meet the specific needs of each client. Our comprehensive range of services includes software development, web design and development, mobile app development, cloud computing, cybersecurity, digital marketing, and skilled resource acquisition. We specialize in helping our clients find the right skilled resources to meet their unique business needs. At Neogencode Technologies, we prioritize communication and collaboration with our clients, striving to understand their unique challenges and provide customized solutions that exceed their expectations. We value long-term partnerships with our clients and are committed to delivering exceptional service at every stage of the engagement. Whether you are a small business looking to improve your processes or a large enterprise seeking to stay ahead of the competition, Neogencode Technologies has the expertise and experience to help you succeed. Contact us today to learn more about how we can support your business growth and provide skilled resources to meet your business needs.
Candid answers by the company
IT & Engineering Talent Staffing
- Provides full-time and contract-based hiring, delivering handpicked, pre‑screened developers across tech stacks—ranging from web, mobile, AI/ML, Web3/blockchain.
- Maintains a bench o vetted candidates, offering fast delivery of interview-ready profiles—often within 24 hours.
- Offers payroll management, handling compliance, tax, attendance, and documentation for both contractors and full-time employees.
2. End-to-End Project Delivery
- Delivers full-stack development solutions: web, mobile, cloud, AI/ML, Blockchain/Web3.
- Manages entire project lifecycle—requirements gathering, design (UI/UX), development, deployment, and ongoing support .
3. Additional Offerings
- Expands into cybersecurity consulting, digital marketing, and cloud platform services (like AWS, GCP, Azure) .
- Provides strategic IT consulting to align technology solutions with business objectives
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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.
Key Skills :
• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through
to React-based user interfaces, deployed on Databricks
• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including
decision capture, audit logging and file exports for downstream systems
• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work
alongside ML models
• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited
outputs
• Writes performant SQL against governed data and ensures services operate within defined access
boundaries
• Builds interactive screens, dashboards and conversational interfaces that let users review and act
on AI recommendations
• Works closely with GenAI/ML engineers, data engineers and BA
Only immediate joiners are considered.
This is an SDE II Full Stack Developer role, but mostly backend: around 70% Python and FastAPI and 30% frontend in React or Angular. You'll build and ship real AI applications such as AI agents, LLM-based workflows, and APIs that connect AI models to web products, using SQL and NoSQL databases on the cloud, mainly Google Cloud. It's not research or prototype work. What you build goes live for enterprise clients, so you'll also own performance, security, and monitoring. You'll report to the Lead Engineer and spend some time each day guiding junior engineers. The role is fully on-site in Chennai from Day 1, with hybrid possible later based on performance. The process has 3 technical rounds (1 virtual and 2 on-site) followed by a salary discussion. The panel focuses on practical system design and real projects you've built, so be ready to explain what business problem you solved and the result it delivered. If you've built and shipped AI-powered backend systems with 4–10 years of experience and want ownership in a fast-moving AI company, this is a strong fit.
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.
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
Key Responsibilities
- Design, develop, and maintain scalable applications using Python.
- Build and integrate AI-powered solutions into existing applications.
- Develop REST APIs and backend services.
- Work with AI/ML models, LLMs, and Generative AI technologies where applicable.
- Integrate AI services and APIs into business applications.
- Write clean, maintainable, and efficient code.
- Collaborate with cross-functional teams to deliver high-quality solutions.
- Troubleshoot issues and optimize application performance.
Must-Have Skills
- Strong hands-on experience in Python development.
- Good understanding of Python frameworks such as FastAPI, Flask, or Django.
- Experience in REST API development and backend services.
- Knowledge or experience in AI/ML concepts.
- Understanding of application development, debugging, and problem-solving.
- Good understanding of databases and data handling.
Good-to-Have Skills
- Hands-on experience with Generative AI and Large Language Models (LLMs).
- Experience with AI APIs and frameworks such as LangChain or LlamaIndex.
- Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
- Familiarity with cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, Kubernetes, or CI/CD pipelines.
Proficient
Python Backend Development
Python, REST APIs, Microservices, FastAPI, Flask, Django, API Design, Authentication, Error Handling
Design, implement, and maintain scalable backend systems using Python frameworks. Build robust REST APIs, ensure secure authentication, and handle errors gracefully. Demonstrate expertise in microservices architecture and API design.
35
Proficient
React JS
React JS, Components, Hooks, State Management, API Integration, Responsive UI, Frontend Testing
Develop responsive and interactive user interfaces using React JS. Effectively use components, hooks, and state management. Integrate APIs and ensure frontend code is well-tested and maintainable.
30
Proficient
Gen AI / Agentic AI
LLMs, Agentic AI, LangChain, LangGraph, Google ADK, Semantic Kernel, Prompt Engineering, Tool Calling, RAG, Embeddings, Vector Search, Memory, Planning, Reasoning, Multi-Agent Systems, Guardrails, Azure OpenAI, Vertex AI, AWS Bedrock
Demonstrate hands-on experience with LLMs and agentic AI frameworks. Build, integrate, and optimize AI agents using modern tools and platforms. Show proficiency in prompt engineering, tool calling, RAG, embeddings, and multi-agent systems.
30
Advanced
Cloud & Deployment
AWS, Azure, GCP, Cloud Deployment, Containers, CI/CD, Application Hosting, Monitoring
Deploy applications to cloud platforms, manage containers, set up CI/CD pipelines, and monitor application health. Demonstrate familiarity with at least one major cloud provider.
Job Description
We are looking for an experienced Python Full Stack – GenAI / Agentic AI Engineer with 5+ 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 OR 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
Job Title : Full-Stack AI Product Engineer
Experience : 3+ Years
Work Mode : Remote
Time Zone : IST
Engagement Type : Freelance
Availability : Must be comfortable attending US client calls during IST night hours.
Role Overview :
We are looking for a Full-Stack AI Product Engineer with hands-on experience building and deploying production-ready AI-powered applications. The ideal candidate should have strong Python backend development skills, practical expertise in LLMs, AI agents, RAG pipelines and tool calling, along with basic frontend development knowledge.
Mandatory Skills :
Python, FastAPI, AI / LLMs, AI Agents, RAG, Tool Calling, PostgreSQL, Redis, Docker, GCP / Cloud Run, CI/CD, Basic React.js / Next.js.
Key Responsibilities :
- Design, develop and maintain AI-powered products using Python and FastAPI.
- Build and integrate LLM-based applications, AI agents, RAG pipelines and tool-calling workflows.
- Develop scalable backend services and REST APIs.
- Work with PostgreSQL and Redis for data storage, caching and performance optimization.
- Containerize applications using Docker and deploy services on GCP, preferably Cloud Run.
- Implement CI/CD pipelines and follow production deployment best practices.
- Develop and integrate basic frontend features using React.js or Next.js.
- Troubleshoot production issues, optimize performance and ensure application reliability.
- Collaborate with US-based clients and stakeholders during IST night hours when required.
Required Skills :
- 3+ years of relevant software development experience.
- Strong proficiency in Python and FastAPI.
- Hands-on experience with AI / LLMs and production-level AI product development.
- Practical experience building AI agents, RAG pipelines and tool / function-calling workflows.
- Good knowledge of PostgreSQL and Redis.
- Experience with Docker, GCP / Cloud Run and CI/CD pipelines.
- Basic working knowledge of React.js or Next.js.
- Understanding of REST APIs, application architecture, deployment and production debugging.
- Excellent problem-solving and communication skills.
Preferred Qualifications :
- Experience deploying and maintaining AI applications in production.
- Familiarity with LLM orchestration frameworks and vector databases.
- Experience with cloud-native application development and monitoring.
Important Requirements :
- Must have demonstrable, hands-on experience delivering production-grade AI products.
- Must be comfortable working remotely and coordinating with US clients during IST night hours.
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.










