Generative AI Engineer

Our client is a trusted global innovator of IT and business services. They help clients transform through consulting, industry solutions, business process services, digital & IT modernization and managed services. Our client enables them, as well as society, to move confidently into the digital future. We are committed to our clients’ long-term success and combine global reach with local client attention to serve them in over 50 countries around the globe.· Job Title: AI Engineer· Location: Bangalore· Experience: 9+ yrs· Job Type : Contract to hire.· Notice Period:- Immediate joiners.Mandatory Skills:Nice to have worked on Pricing domain with in Medcare company, mainly worked on Developing AI solutions on PricingRole Overview We are seeking a highly capable AI Engineer (Contract) to design, build, deploy, and govern enterprise-grade Generative AI solutions. This role requires a rare combination of hands-on technical execution, AI delivery leadership, and the ability to translate complex AI concepts into clear, measurable business value. You will play a critical role in advancing the organisation’s AI roadmap, contributing immediately by delivering secure, scalable, and responsible AI solutions across the Microsoft AI ecosystem and leading open-source frameworks, within a regulated enterprise environment. This role is best suited to an experienced AI contractor who is comfortable owning delivery end to end and operating at pace in complex, real-world settings. The Role As an AI Engineer (Contract), you will take ownership of the end-to-end delivery of Generative AI solutions—from use-case discovery and architecture through to production deployment and monitoring. You will work closely with business stakeholders, data engineers, and platform teams to turn high-value opportunities into production-ready AI solutions that deliver tangible outcomes. Immediate impact, strong delivery discipline, and technical credibility are essential. Key Responsibilities AI Solution Design & Delivery • Design, build, and deploy end-to-end Generative AI solutions using Microsoft Power Platform, Copilot Studio, Azure AI Foundry, MS Purview and MS Fabric. • Lead delivery of custom enterprise copilots and GenAI applications, integrating structured and unstructured enterprise data. • Architect and implement AI solutions leveraging Azure OpenAI Service and other Azure AI services. • Drive delivery from use-case definition and solution design through to production deployment and live monitoring. • Translate real operational problems into practical, scalable GenAI architectures with measurable business impact. Hands-On Engineering & Execution • Develop and maintain AI/ML solutions using Python and SQL, applying strong software engineering discipline. • Implement Retrieval-Augmented Generation (RAG), prompt engineering, agentic workflows, and LLM fine-tuning using structured and unstructured data. • Work with open-source AI frameworks such as Hugging Face, CrewAI, and related orchestration or agent frameworks. • Integrate AI capabilities via APIs, data connectors, and enterprise gateways. • Work with vector databases and embedding models to support semantic search and knowledge retrieval. Platform, LLMOps, MLOps & DevOps • Deploy and operate AI solutions across cloud platforms (Azure preferred; AWS or GCP acceptable). • Establish and work within LLMOps / MLOps pipelines, including model versioning, evaluation, observability, and lifecycle management. • Implement and maintain CI/CD pipelines for AI projects using GitHub and Azure DevOps tooling. • Ensure AI solutions are secure, scalable, resilient, and production-ready, aligned with enterprise standards. Governance, Security & Responsible AI • Embed AI governance, Responsible AI principles, and ethical AI practices into solution design and delivery. • Ensure compliance with security, privacy, and regulatory requirements, leveraging Microsoft Purview and related controls where applicable. • Operate effectively within regulated environments, contributing to the practical implementation of AI governance, not just theoretical frameworks. • Partner with risk, legal, and compliance stakeholders to support production deployment of AI solutions. Stakeholder Engagement & Communication • Act as a bridge between technical teams and business stakeholders, explaining complex AI concepts in simple, actionable terms. • Provide pragmatic recommendations, trade-offs, and delivery updates to support decision-making. • Enable teams to confidently adopt and operationalise AI solutions. Required Skills & Experience Core Technical Skills • 3+ years’ experience in software engineering, data science, or machine learning. • 2+ years’ hands-on experience delivering Generative AI / LLM-based solutions in production environments. • Strong hands-on experience with: o Power Platform (Power Apps, Power Automate) o Copilot Studio / Microsoft 365 Copilot o Azure AI Foundry o Azure OpenAI Service o Microsoft Purview • Strong proficiency in Python and SQL. • Proven experience with prompt engineering, LLM fine-tuning, and optimisation techniques. • Practical experience with open-source AI frameworks (e.g. Hugging Face, CrewAI, LangChain-style tools). • Solid understanding of model deployment, monitoring, and lifecycle management. AI, Data Science & ML • Strong foundation in data science, machine learning, NLP and LLM concepts. • Experience building and operationalising AI/ML solutions in real-world business contexts. • Ability to evaluate model performance, bias, risk, and suitability for enterprise use cases. Governance & Enterprise Readiness • Demonstrated experience working with AI governance, Responsible AI, security, and privacy controls. • Understanding of enterprise data management, access controls, and compliance requirements in regulated environments.

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