AI Implementation Engineer

Wissen Technology is hiring for AI Implementation Engineer
About Wissen Technology:
At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.
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.
Experience: 6 - 12 Years
Location: Bangalore/Mumbai
Mode of Work: Hybrid
Education Qualification: MCA/B.E/B.Tech/MTech
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
Wissen Sites:
Website: www.wissen.com
LinkedIn: Wissen Technology | LinkedIn
Wissen Leadership: Leadership Team | Wissen
Wissen Live: LinkedInログイン | LinkedIn
Wissen Thought Leadership: https://www.wissen.com/articles

Work arrangement
Hybrid