AI Integration Engineer

Confidential

Pune, Mahārāshtra, India permanent

Posted: April 7, 2026

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Quick Summary

Builds the connective tissue between LLM APIs, existing product systems, and end users by integrating, orchestrating, and deploying AI capabilities into production software reliably, securely, and at scale.

Required Skills

Backend Development API Integration LLM API Integration RAG Pipelines Agentic Workflows Prompt Engineering Prompt Evaluation Performance Monitoring API Security Cloud Platforms Prompt Versioning LLM Output Guardrails

Job Description

The AI Integration Engineer builds the connective tissue between LLM APIs, existing product systems, and end users. They are not training models. They are 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 in the SDLC, from spec to CI/CD to production

observability

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