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.

Requirements

- Experience: 6 - 12 Years

- Location: Bangalore/Mumbai

- Mode of Work: Hybrid

- Education Qualification: MCA/B.E/B.Tech/MTech

- Job Type: Full time

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 robust 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, Lang Chain, Lang Graph, or Microsoft Agent Framework

- Define, monitor, and improve quality metrics, model evaluations, and program-level AI delivery KPIs

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.

📌 AI Implementation Engineer (Bengaluru)
🏢 Wissen Infotech
📍 Bengaluru