Senior AI Solutions Engineer

About AI & Data Science Office

AI & Data Science Office brings together data science, advanced analytics, and AI expertise across IQVIA's international markets.

We work with Commercial Solutions teams to transform business needs into scalable solutions that improve client offerings, operational efficiency, and decision-making. Our work spans advanced analytics, machine learning, AI, Generative AI (GenAI), and agentic AI, supported by healthcare data, engineering, and domain expertise.

We 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.

About the Role

We are seeking an experienced Senior AI Solutions Engineer to design, develop, evaluate, and deploy AI, machine learning, GenAI, and agentic AI solutions that address complex business and client challenges.

Working closely with business stakeholders, data scientists, and technology teams, you will identify opportunities where AI can create measurable value and translate them into practical, production-ready solutions.

From proof of concept to deployment and adoption, you will play a key role in shaping AI capabilities across IQVIA's international markets.

Key Responsibilities

• 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.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Experience designing and deploying AI, machine learning, advanced analytics, or GenAI solutions in production environments.
• 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 practices.
• Ability to communicate technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications

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

What You'll Bring

• Passion for applying AI technologies to real-world business challenges.
• A builder's mindset and ability to move from concept to deployment.
• Curiosity about emerging technologies and continuous learning.
• Strong collaboration and stakeholder management skills.
• Focus on delivering practical, scalable, and measurable business outcomes.