Apply for AI Integration Engineer at Leapfrog Technology in Kathmandu, Nepal. Full-time opportunity. Explore requirements and apply online on SpireJob Nepal.
The AI Integration Engineer builds the connective tissue between LLM APIs, existing product systems, and end users. They integrate, orchestrate, and deploy AI capabilities into production software reliably, securely, and at scale. Qualification and Experience: 3+ years backend or full-stack experience; strong API design and consumption skills. Proven experience integrating LLM APIs (any major provider) into production applications. 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, cost management for LLM-based services. Experience with AWS or another major cloud platform. 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 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 in the SDLC, from spec to CI/CD to production observability.
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