AI Integration Engineer

• We are seeking an experienced AI Integration Engineer to build and deploy AI-powered capabilities into production applications
• The ideal candidate will have strong experience integrating Large Language Model (LLM) APIs, designing Retrieval-Augmented Generation (RAG) pipelines, and building scalable AI workflows
• This role requires collaboration with cross-functional engineering teams to deliver secure, reliable, and production-ready AI solutions that enhance user experiences
• Job Responsibilities Integrate LLM APIs such as OpenAI GPT-4o, Anthropic Claude, AWS Bedrock, and Google Gemini into backend services and user-facing applications
• Design and implement RAG pipelines, including document ingestion, chunking strategies, vector database integration, and retrieval optimization
• Build and maintain agentic AI workflows using frameworks such as LangChain, LlamaIndex, AgentCore, CrewAI, or custom orchestration patterns
• Develop and manage prompt engineering strategies, prompt versioning, and prompt evaluation frameworks
• Implement AI guardrails, including output validation, content filtering, fallback mechanisms, and safety controls
• Monitor AI application performance, including latency, token usage, cost optimization, and model accuracy
• Collaborate with frontend and backend engineering teams to integrate AI capabilities into product workflows
• Manage the AI integration lifecycle from design and development through CI/CD, deployment, monitoring, and production support
• Required Skills 3+ years of Backend or Full Stack development experience with strong API design and integration skills
• Proven experience integrating LLM APIs (OpenAI, Anthropic, AWS Bedrock, Google Gemini, or similar) into production applications
• Strong programming skills in Python and/or TypeScript/Nodejs
• Hands-on experience designing and implementing RAG architectures using vector databases such as Pinecone, Weaviate, pgvector, or similar
• Strong understanding of prompt engineering, including system prompts, few-shot prompting, structured outputs, and prompt optimization
• Experience with API security, authentication, rate limiting, and LLM cost management
• Experience working with AWS or another major cloud platform
• Strong troubleshooting, debugging, and problem-solving skills
• Preferred Skills Experience with AI agent frameworks such as LangChain, LlamaIndex, AgentCore, CrewAI, AutoGen, or similar
• Familiarity with multimodal AI capabilities, including vision, audio, function calling, and tool integration
• Understanding of AI model fine-tuning concepts and workflows
• Experience using AI-assisted development tools to improve engineering productivity
• Exposure to CI/CD pipelines, containerization, and cloud-native application deployment
• Soft Skills Excellent communication and interpersonal skills
• Strong collaboration and stakeholder management abilities
• Self-driven with a strong sense of ownership, accountability, and continuous learning

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.