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 Pricing

Role 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 organisations 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 solutionsfrom 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.