We’re looking for an experienced AI Full-Stack Engineer with a passion for building next-generation intelligent applications. You’ll work at the intersection of cloud-native development, modern AI technologies, and scalable backend systems - designing and deploying AI-enabled applications that integrate LLMs, RAG architectures, agentic AI, and vector-based knowledge retrieval., * Design, develop, and maintain scalable full-stack Generative AI and Agentic AI applications

• Build responsive UIs and integrate them with APIs, AI services, and enterprise systems
• Collaborate with architects, product owners, and engineering teams to translate business needs into technical solutions

API & Cloud-Native Development

• Design and develop RESTful and/or GraphQL APIs
• Build, deploy, and maintain applications on AWS
• Implement microservices architectures with containerization, orchestration, observability, and infrastructure automation

AI-Enabled Applications

• Integrate AI-driven capabilities using modern AI frameworks and cloud services
• Build LLM-powered solutions for conversational experiences, intelligent automation, and knowledge discovery
• Design RAG architectures and optimize prompts, model interactions, and retrieval strategies

️ Agentic AI & Intelligent Workflows

• Design autonomous agent-based workflows that orchestrate services and support decision-making
• Build AI agents that interact with APIs, databases, and enterprise systems
• Implement multi-step reasoning, planning, and workflow automation

Vector Databases & Knowledge Retrieval

• Build semantic search and vector-based retrieval capabilities
• Work with vector databases and search platforms
• Develop pipelines for document ingestion, embedding generation, indexing, and semantic retrieval

Model Context Protocol (MCP) Development

• Design, develop, and deploy MCP servers and services for secure AI-to-enterprise integration
• Build reusable MCP-enabled connectors for contextual access to enterprise systems

️ AI-Assisted Development & DevOps

• Leverage AI-powered development tools to boost engineering productivity
• Design and maintain CI/CD pipelines for automated build, testing, deployment, and monitoring
• Support infrastructure automation using IaC and cloud-native DevOps services

Bachelor’s degree in Computer Science, Engineering, IT, or related field

7+ years of full-stack software development experience, with 3+ years focused on Generative AI and/or Agentic AI

Hands-on experience building and deploying LLM-powered applications

Demonstrated experience with RAG architectures and knowledge retrieval systems

Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or similar AI frameworks

Experience with vector databases and semantic search technologies

Experience developing AI agents and agent orchestration frameworks

Experience designing MCP servers, connectors, or related AI integration frameworks

Experience with AWS AI/ML services (Amazon Bedrock, SageMaker, Amazon Q Developer, etc.)

Strong AWS cloud architecture, deployment, and operations experience

Experience with Docker and Kubernetes

Frontend experience with React, Angular, or Vue.js

Backend experience with Python, Node.js, Java, or comparable technologies

Experience with RESTful APIs, GraphQL, and microservices

Experience with AI-assisted development tools (Claude Code, Codex, Cursor, Cline, GitHub Copilot, or similar)

CI/CD pipeline and DevOps best practices experience

Knowledge of prompt engineering, model evaluation, AI governance, and responsible AI

Experience with observability, monitoring, and telemetry platforms

Bonus Points

Master’s degree in CS, AI, Data Science, or related discipline

AWS, Azure, Kubernetes, or AI/ML certifications

Experience building enterprise-scale AI applications in regulated or highly secure environments

Familiarity with hybrid cloud and multi-cloud architectures

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