Full Stack AI Engineer

Daten; India; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

A technology solution provider is seeking a Full Stack AI Engineer to design, build, and deploy next-generation agentic AI applications leveraging Large Language Models and AWS services. The role involves working across the entire AI application lifecycle, from backend API development to frontend web interface creation. Candidates must have strong expertise in AI development and cloud technologies, with hands-on experience in the essential tools and frameworks. This position is based in Dadri, Uttar Pradesh, India.

Qualifications

• Hands-on experience with LLM fine-tuning and inference.
• Strong expertise in AI agent development and prompt engineering.
• Experience building production-grade GenAI applications.

Responsibilities

• Design and implement multi-agent pipeline systems.
• Develop and manage agentic workflows using frameworks.
• Fine-tune and adapt LLMs using custom enterprise data.
• Implement advanced prompt engineering strategies.
• Build and maintain Python-based backend APIs.
• Develop intuitive and responsive web interfaces.
• Integrate frontend components with AI-driven backend APIs.
• Deploy and operate full-stack AI applications on AWS.

Skills

LLM fine-tuning and inference

AI agent development

Prompt engineering

React.js

Vue.js

Tools

LangChain

AWS Strands

Flask

FastAPI

AWS Bedrock

S3

Lambda

EC2

Job description

We are seeking aFull Stack AI Engineerto design, build, and deploy next-generationagentic AI applicationsleveraging Large Language Models (LLMs), multi-agent orchestration frameworks, and cloud-native AWS services. This role requires deep expertise in Python-based AI backends, LLM fine-tuning and integration, modern frontend frameworks, and scalable AWS deployments.

The ideal candidate will operate across theentire AI application lifecycle—from model fine-tuning and agent workflow design to frontend development and production-grade cloud deployment.

Key Responsibilities

AI / Agentic Systems

• Design and implementmulti-agent pipeline systemsfor complex reasoning, orchestration, and task execution.
• Develop and manageagentic workflowsusing frameworks such asLangChain, AWS Strands, or similar.
• Fine-tune and adaptLLMsusing custom enterprise data onAWS Bedrock and/or OpenAIplatforms.
• Implement advancedprompt engineeringstrategies for task decomposition, tool calling, and agent collaboration.
• Build and maintainPython-based backend APIsusingFlask or FastAPI.
• Integrate LLM inference, vector search, memory, and agent logic into scalable backend services.
• Develop ML pipelines for data preprocessing, embedding generation, evaluation, and inference.
• Read, analyze, and interface with existingJava-based services or codebasesas required.

Frontend Development

• Develop intuitive and responsiveweb interfacesusingReact.js or Vue.js.
• Integrate frontend components with AI-driven backend APIs for real-time inference and agent interactions.
• Collaborate with UX and product teams to translate AI workflows into usable customer experiences.
• Deploy and operate full-stack AI applications onAWS, leveraging:
  • AWS Bedrockfor LLM access and fine-tuning
  • S3for data and artifact storage
  • Lambdafor serverless workflows
  • EC2for scalable compute workloads
• Implement secure, scalable, and cost-optimized cloud architectures.
• Support CI/CD pipelines and production monitoring for AI services.

Requirements

Required Skills

AI / ML

• Hands-on experience withLLM fine-tuning and inference(AWS Bedrock, OpenAI).
• Strong expertise inAI agent developmentandprompt engineering.
• Experience building production-gradeGenAI applications.

Agent Frameworks

• Practical experience withLangChain, AWS Strands, or equivalent agent orchestration frameworks.
• Experience withFlask/FastAPI, ML pipelines, and large-scale data processing.
• Ability toread and analyze Java codefor integration or enhancement.

Frontend

• Strong working knowledge ofReact.js or Vue.js.
• Experience building AI-integrated web applications.
• Hands-on experience withAWS Bedrock, S3, Lambda, EC2.
• Understanding of cloud security, scalability, and performance best practices.

Nice-to-Have Skills

• Deep experience inGenAI application developmentbeyond PoCs.
• Exposure tomulti-agent system architecturesin production environments.
• Experience designingagentic workflowsfor enterprise-scale use cases.
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
• MLOps and model evaluation experience.