Full Stack Gen AI Engineer

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.

Job Description:

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

Key Responsibilities:

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

Required Skills:

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

Preferred Experience:

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

Generative AI Engineer 

Role Overview:

You will be responsible for the hands-on development, coding, and deployment of AI-powered features. Your focus is on writing clean, efficient code to integrate LLMs into our existing tech stack, building robust data pipelines for RAG, and ensuring the reliability of model outputs through rigorous testing and optimization.

Key Responsibilities

• Application Implementation: Code and integrate LLM APIs (OpenAI, Anthropic, etc.) or local models into backend services using Python, FastAPI, etc.,
• MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript) to expose internal databases, APIs, and file systems to AI agents.
• RAG Implementation: Build and maintain the "plumbing" for Retrieval-Augmented Generation—specifically coding the data ingestion scripts, text chunking logic, and metadata filtering.
• Vector DB Management: Perform day-to-day operations on vector databases (Pinecone, Milvus, etc.), including indexing, querying, and optimizing search retrieval.
• Prompt Programming: Develop, version-control, and refine complex prompt templates (using Jinja2 or similar) to ensure consistent structured outputs (JSON/YAML).
• Agent Development: Implement multi-step workflows using LangChain, LangGraph, CrewAI etc.,, focusing on tool-calling logic and error handling.
• Evaluation & Testing: Build automated test suites to detect "hallucinations" and measure accuracy using frameworks.
• Performance Tuning: Implement caching layers and streaming responses to reduce latency and improve the end-user experience; Token optimization.
• Data Pre-processing: Clean and tokenize datasets for model fine-tuning or high-quality context retrieval.

Technical Skills (The "Execution" Stack)

• Language: Advanced Python (Asyncio, Pydantic) and optional TypeScript/Node.js (for full-stack integration).
• AI Frameworks: Hands-on experience with any of LangChain, LlamaIndex, and Hugging Face Transformers. RAG and Vector search concepts.
• Data Handling: Proficiency in SQL and handling unstructured data formats (PDFs, Markdown, JSON).
• Deployment: Practical experience with Docker, GitHub Actions (CI/CD), and experience with OpenTelemetry, LangSmith, Weights & Biases etc., Understanding of evaluation/guardrails.
• MCP/API Proficiency: Deep understanding of RESTful APIs, Streaming HTTP, MCP server vs client, JSONRPC

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.

Location: Jaipur (Work From Office)

Employment Type: Full-Time

We're looking for a GenAI Engineer (LLM Engineer) to build scalable AI-powered SaaS applications using Large Language Models (LLMs). You'll develop intelligent AI workflows, integrate LLMs into production systems, and build secure, high-performance AI solutions.

Key Responsibilities

• Integrate LLM APIs (OpenAI, Claude, Hugging Face) into production applications.
• Design and optimize RAG pipelines and prompt engineering workflows.
• Build and manage Vector Databases (Pinecone, Weaviate, pgvector).
• Optimize AI performance, latency, and operational cost.
• Ensure secure, scalable AI architecture.
• Collaborate with Product and Engineering teams to deliver AI-powered features.

Requirements

• 3+ years of backend development using Python, Go, or Node.js.
• Hands-on experience with LLMs, LangChain or LlamaIndex.
• Strong understanding of RAG, Prompt Engineering, and Vector Databases.
• Experience with AWS, GCP, or Azure.
• Knowledge of APIs, Microservices, and AI application development.

Preferred: Experience in SaaS/FinTech, LLMOps, or Model Fine-tuning.

Education: B.Tech, BCA, or equivalent technical qualification.

Apply Now

Application Form: https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort

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.

Apply: https://processity.ai/careers/fullstack-ai-engineer

BigMantra is a Vertical Autonomous AI Agent Builder — we build AI companies that go a mile deep into specific industries. Our products include Mantra Spaces (AI-powered UK HMO property management) and Verity Law (AI-powered legal conveyancing). Our team is small, our stack is modern, and your code ships to production the same week you write it.

We're looking for a Fullstack AI Applied Engineer who can build full applications end-to-end and wire AI agents into production systems that real users depend on.

WHAT YOU'LL DO

• Build and ship full-stack web applications using React / Next.js and Python / Node.js

• Design and implement AI agent workflows using LangChain, LangGraph, Claude Agent SDK, Agno, or similar

• Integrate agents with real-world APIs — Salesforce, Google Workspace, WhatsApp Business, email providers

• Build and optimize database layers — production SQL, schema design, RAG pipelines

• Own deployment and infrastructure — Docker services, CI/CD pipelines on AWS or Azure

• Write tests that matter — E2E, load tests, performance benchmarks

• Collaborate directly with the founding team on architecture and product direction

MUST HAVE

• 3+ years of professional software engineering experience

• Strong JavaScript / TypeScript — React, Next.js, Node.js in production

• Strong Python — backends, agent systems, data pipelines

• Hands-on experience with at least one AI agent framework (LangChain, LangGraph, Claude Agent SDK, Agno, or equivalent)

• Docker services for containerization and deployment

• CI/CD pipelines — GitHub Actions, GitLab CI, or similar

• Deployment experience on AWS or Azure

• Solid SQL and database skills — schema design, query optimization

GOOD TO HAVE

• Experience with autonomous agents — MCP (Model Context Protocol), skills, plugins, tool-use

• Memory and context management for long-running agents

• Prompt engineering and optimization

COMPENSATION & BENEFITS

• ₹30L – 50L per annum (based on experience)

• Equity / ESOPs — early-stage participation

• Remote-friendly — Coimbatore office available

• Learning budget — courses, conferences, AI tooling subscriptions

• Flexible hours — output over seat time

Role: AI Developer

Experience: 3–4 Years

Employment Type: Full-Time

Location: Goregaon, Mumbai

About the Role

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

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

Key Responsibilities

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

Required Skills

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

Good to Have

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

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.

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.