Full Stack Developer (Agentic AI)

As a Full Stack Engineer (Agentic AI), you will be at the forefront of building cutting-edge AI-powered applications using modern technology stacks. This position involves working with multi-agent orchestration frameworks, LLM observability systems, Langfuse, Agno, MCP tools, and advanced retrieval & evaluation pipelines.

You'll collaborate closely with AI product and platform teams to deliver high-quality, production-grade solutions that serve customers across the Asia-Pacific region. This role transcends traditional full-stack engineering by focusing on AI-native backend services, agentic workflows, guardrails, evaluation pipelines, and front-end interfaces that empower both customers and internal users.

Key Responsibilities:

Agentic AI & Backend Engineering

• Multi-Agent Systems: Build sophisticated multi-agent AI systems using frameworks such as Agno,
• Langchain, and LlamaIndex, MCP Integration: Implement Model Context Protocol (MCP) tools for ehanced agentic capabilities
• API Development: Build and maintain robust APIs using Node.js/TypeScript, deployed on AWS infrastructure (Serverless, Lambda, ECS)
• LLM Integration: Integrate Large Language Models (OpenAI, Claude) into backend services with best practices for prompt engineering, safety protocols, and guardrails
• Quality Assurance: Implement LLM evaluations, automated regression testing, benchmarking, and quality scoring systems
• Data Management: Work with vector databases (Pinecone, Qdrant, Weaviate) and develop retrieval pipelines
• Observability: Build comprehensive observability integrations using Langfuse, including traces, spans, scoring, and analytics

Frontend Engineering

• Modern UI Development: Create clean, intuitive user interfaces using React, Next.js, and TypeScriptDashboards: Build comprehensive dashboards for agentic workflows, analytics, observability, and internal tools
• Design Integration: Integrate UX workflows using Figma; experience with AI-assisted development
• through Cursor/Copilot is advantageous
• DevOps, Cloud & Infrastructure
• Microservices Deployment: Deploy and scale microservices on Cloud Run, AWS ECS, Kubernetes, and similar platforms
• CI/CD Pipeline Management: Build secure, scalable continuous integration and deployment pipelines using GitHub Actions
• Distributed Systems: Work extensively with APIs, Webhooks, Pub/Sub, EventBridge, and distributed system architectures
• Security: Implement comprehensive guardrails including LLM Guard, custom rule engines, and safety layers

Collaboration & AI Culture

• Cross-Functional Teamwork: Collaborate effectively with Product, Operations, and Finance teams
• Innovation: Engage in brainstorming sessions, rapid prototyping, and hackathons
• Culture Building: Contribute to Asurion's AI-first engineering culture by adop ing new tools and sharing best practices

Required Qualifications:

Technical Skills

• Core Programming: Strong proficiency in Node.js, TypeScript, React, and Next.js
• AI Systems: Hands-on experience building Agentic AI systems or LLM-based applications
• Orchestration Frameworks: Familiarity with Agno, LangChain, LangGraph, or similar orchestration frameworks
• Tools: Experience with Model Context Protocol (MCP) tools
• Observability: Strong understanding of LLM Observability systems (Langfuse preferred)
• AI Engineering: Experience with LLM evaluations, RAG patterns, prompt engineering, and guardrails
• API Development: Proficiency in REST and GraphQL API development
• Cloud Platforms: Practical experience with Amazon Web Services (AWS)
• Database Management: Experience with PostgreSQL, MongoDB, Redis, and vector databases
• DevOps Skills: Good grasp of CI/CD processes, testing frameworks, containerization (Docker), and GitHub
• workflows
• Vibe Coding: Ability to work effectively with Cursor, GitHub Copilot, or other AI-assisted development
• toolsSoft Skills
• Leadership Qualities: Strong ownership, accountability, and problem-solving mindset
• Agile Methodology: Ability to thrive in fast-paced Agile team environments
• Continuous Learning: Passion for learning new technologies within the rapidly evolving AI ecosystem
• Communication: Excellent communication and collaboration skills