Lead Data & AI Engineer

Grow your career internally at Qualys, our best talent comes from within!

Job Description

Design, build, and scale enterprise-grade AI/GenAI solutions that leverage enterprise data platforms and business applications to automate processes, enhance decision-making and deliver measurable business outcomes. This role focuses on defining and implementing the foundational AI strategy for the CIO organization by combining AI technologies, modern data platforms, enterprise systems, APIs, and analytics in a secure, scalable, and production-ready environment. The ideal candidate brings experience building AI solutions on platforms such as Data Lake or Lakehouse architectures and can bridge business, data and technology teams to drive enterprise-wide AI adoption and innovation.

Responsibilities

• Define and help execute the Enterprise AI strategy and roadmap across enterprise applications, data platforms and enterprise workflows.
• Design, develop and deploy AI/GenAI applications, RAG solutions, intelligent agents and workflow automation leveraging enterprise data and modern AI technologies.
• Leverage modern Data Lake, Lakehouse and cloud data platforms to design, implement and scale AI solutions using enterprise data.
• Build AI capabilities on top of enterprise data platforms, including structured, unstructured, and real-time data sources, enabling scalable and governed AI adoption.
• Architect backend services, APIs, integrations, and orchestration frameworks using LLMs, model APIs, enterprise systems and governed data.
• Define AI governance, evaluation, observability and performance frameworks to ensure quality, security, reliability, and business value.
• Collaborate with Business and Enterprise Application teams to identify and deliver high-impact AI use cases.
• Rapidly prototype and scale AI solutions into secure, production-ready deployments while optimizing performance, scalability, and cost.
• Develop reusable AI frameworks, architecture patterns, and best practices that accelerate enterprise-wide AI innovation and adoption.

Required Qualifications

• 7–12+ years of experience in Software Engineering, AI/ML, or GenAI application development.
• Proven experience designing and implementing AI/ML or GenAI solutions on modern cloud-based data platforms such as Snowflake, Databricks, OCI, Lakehouse, data lake or enterprise analytics ecosystems.
• Strong understanding of enterprise Data Architectures, Data Lakes, Lakehouse, semantic layers, data pipelines, governance, and AI-ready data foundations.
• Strong expertise in Python, backend development, APIs, system integration, and workflow orchestration.
• Hands-on experience with RAG, LLMs, prompt engineering, tool/agent calling, AI evaluation, and observability.
• Experience integrating enterprise applications, data platforms, and services using APIs and event-driven architectures.
• Strong analytical, systems thinking, and problem-solving skills with the ability to translate ambiguous business problems into scalable AI solutions.

Preferred Qualifications

• Experience with vector databases, embeddings, semantic search, and advanced RAG architectures.
• Experience designing and implementing AI/GenAI solutions leveraging enterprise Data Lakes, Lakehouse, and large-scale analytical data platforms.
• Understanding of data governance, semantic layers, data quality, lineage, security, and compliance considerations required for enterprise AI implementations.
• Knowledge of SQL, data engineering, and data pipelines.
• Experience integrating AI into enterprise applications and business workflows.
• Exposure to intelligent agents, automation platforms, and AI governance frameworks.
• Experience building reusable AI frameworks, accelerators, or enterprise AI platforms.

Educational Qualification

BE/B.Tech/MCA, preferably in Computer Science, Information Technology, or a related field.