Senior AI Solutions Engineer

AI & Data Science Office brings together data science, advanced analytics, and AI expertise across IQVIA's international markets. They work with Commercial Solutions teams to transform business needs into scalable solutions that improve client offerings, operational efficiency, and decision-making. Their work spans advanced analytics, machine learning, AI, Generative AI (GenAI), and agentic AI, supported by healthcare data, engineering, and domain expertise. They connect global innovation with local market needs, accelerate the reuse of proven solutions, and establish shared methodologies, models, and architectural standards across teams and geographies.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.
• Experience designing and deploying AI, machine learning, advanced analytics, or GenAI solutions in production.
• Strong understanding of AI, machine learning, Generative AI, LLMs, prompt engineering, and agentic AI concepts.
• Experience building solutions using modern AI frameworks and tools.
• Knowledge of RAG, vector databases, semantic search, and knowledge retrieval techniques.
• Experience integrating AI solutions with enterprise systems, APIs, and cloud platforms.
• Strong software engineering and solution development skills.
• Understanding of AI governance, evaluation, monitoring, security, and compliance.
• Ability to communicate technical concepts to technical and non-technical stakeholders.

Nice to have:

• Experience building AI-powered products or client-facing AI solutions.
• Familiarity with orchestration frameworks, AI agents, and multi-agent systems.
• Experience with structured and unstructured enterprise data.
• Knowledge of predictive analytics, machine learning, advanced analytics methodologies.
• Knowledge of Responsible AI, model governance, compliance, and risk management.
• Experience in healthcare, life sciences, commercial analytics, or consulting.
• Familiarity with MLOps and LLMOps practices.

• Design, develop, evaluate, and deploy AI, machine learning, GenAI, and agentic AI solutions.
• Translate business requirements into scalable technical solutions and implementation plans.
• Build intelligent workflows leveraging machine learning models, LLMs, enterprise data, APIs, and agentic frameworks.
• Develop solutions involving RAG, semantic search, knowledge discovery, intelligent automation, and decision support.
• Define evaluation approaches to assess solution quality, performance, business impact, and risk.
• Partner with business, analytics, and technology teams throughout the solution lifecycle.
• Transform successful proofs of concept into reusable, production-ready capabilities.
• Integrate AI solutions with enterprise platforms, data sources, and analytical products.
• Apply best practices in software engineering, MLOps, LLMOps, security, governance, and documentation.
• Contribute to reusable frameworks, methodologies, standards, and best practices.
• Support adoption of AI capabilities across markets and business units.
• Evaluate emerging AI technologies and identify opportunities to create business value.

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