Software Engineer 2
15 hours ago
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 , 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, , 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 , TypeScript, React, and
- 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
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