AI Implementation Engineer

Job Summary:

We are hiring an AI Implementation Engineer to build, deploy, and scale enterprise grade Generative AI solutions across business-critical applications. The role involves developing production-ready AI systems using Azure AI services, Large Language Models (LLMs), RAG architecture, and agent-based frameworks while collaborating closely with engineering teams to drive AI adoption and innovation.

Key Responsibilities & Duties:

• Python programming (6+ years) including asynchronous programming and backend application development
• Java and Spring Framework (3+ years) for enterprise-scale application integration
• Azure OpenAI Service, Azure AI Foundry, and Azure AI Search for production GenAI applications
• Retrieval Augmented Generation (RAG) architecture including embeddings, chunking, vector databases, reranking, and grounding techniques
• Agent Frameworks such as Microsoft Agent Framework, Semantic Kernel, AutoGen, Lang Chain, or Lang Graph
• Snowflake and Cortex AI (Cortex Search, LLM Functions) with strong SQL expertise
• Prompt Engineering, LLM evaluation frameworks, testing, and model performance optimization
• DevOps and Cloud Deployment using Azure DevOps, GitHub Actions, Docker, AKS, Azure Functions, and observability tools

Good to Have:

• React.js for AI-powered user interfaces and conversational applications
• Azure AI Content Safety and Responsible AI implementation experience
• Financial Services, Banking, or other regulated industry domain experience
• Real-time streaming applications and token-level LLM operations
• Performance optimization, caching strategies, and cost optimization for AI workloads
• Microsoft Azure AI Engineer Associate Certification

Nice to Have:

• Education: BE/BTech/ME/MTech in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or related field
• Leadership: Experience mentoring engineering teams and driving AI adoption across development squads
• Ownership: Proven track record of delivering end-to-end AI solutions from concept to production deployment
• Problem-Solving: Strong analytical thinking with demonstrated ability to resolve complex AI implementation challenges
• Communication: Excellent written and verbal communication skills with the ability to collaborate across technical and business teams
• Quality Focus: Experience implementing evaluation frameworks, guardrails, monitoring, and observability for AI systems
• Collaboration: Ability to work within cross-functional product engineering teams and enable knowledge transfer

Preferred Experience:

• Design, develop, and deploy enterprise-grade Generative AI solutions using Azure OpenAI, Azure AI Foundry, and Azure AI Search
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines, AI agents, APIs, and enterprise application integrations
• Collaborate closely with engineering delivery pods to accelerate AI adoption and provide hands-on technical guidance
• Implement production-grade AI capabilities including evaluation frameworks, observability, guardrails, caching, and CI/CD pipelines
• Integrate AI systems securely with enterprise data platforms while ensuring compliance, access control, and secrets management
• Optimize AI applications for grounding accuracy, latency, scalability, reliability, and operational cost
• Build and maintain agent-based solutions using Semantic Kernel, AutoGen, LangChain, LangGraph, or Microsoft Agent Framework
• Define, monitor, and improve quality metrics, model evaluations, and program-level AI delivery KPIs