AI Integration Engineer

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  • Colombo, Sri Lanka
  • Full-Time
  • Remote
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Job Description:

Job Description

The AI Integration Engineer builds the connective tissue between LLM APIs, existing product systems, and end users. This is not a model training role — it's about integrating, orchestrating, and deploying AI capabilities into production software, reliably, securely, and at scale.

Key Responsibilities

  • Integrate LLM APIs (Anthropic Claude, OpenAI GPT-4o, AWS Bedrock, Google Gemini) into backend services and user-facing products
  • Design and implement RAG pipelines: document ingestion, chunking strategy, vector store selection, retrieval tuning
  • Build agentic workflows using frameworks such as AgentCore, LangChain, LlamaIndex, or custom orchestration patterns
  • Manage prompt engineering, prompt versioning, and prompt evaluation frameworks
  • Implement guardrails for LLM outputs: validation, content filtering, fallback logic
  • Monitor AI system performance: latency, cost-per-query, accuracy drift, token usage
  • Collaborate with frontend engineers to surface AI capabilities in product UIs
  • Own the AI integration layer across the SDLC, from spec through CI/CD to production observability

Job Requirements

  • 3+ years backend or full-stack experience; strong API design and consumption skills
  • Proven experience integrating LLM APIs (any major provider) into production applications, not just prototypes
  • Proficiency in Python and/or TypeScript/Node.js
  • Hands-on experience with RAG: vector databases (Pinecone, Weaviate, pgvector, etc.), embedding models, chunking strategies
  • Understanding of prompt engineering: system prompts, few-shot examples, chain-of-thought, structured output
  • Solid grasp of API security, rate limiting, and cost management for LLM-based services
  • Experience with AWS or another major cloud platform

Desirable Skills

  • Experience with agentic frameworks: AgentCore, LangChain, LlamaIndex, CrewAI, AutoGen, or similar
  • Familiarity with multi-modal AI (vision, audio) or function calling / tool use
  • Understanding of fine-tuning workflows, even if not hands-on
  • Experience using AI coding assistants to accelerate personal development workflow