I help organizations move from AI curiosity to AI capability.

My work focuses on designing practical AI systems that improve workflows, reduce operational friction, and support better decision-making.

I collaborate with leadership teams to:

• Identify automation opportunities

• Design AI-assisted processes

• Train teams on responsible AI usage

• Implement scalable AI workflows

With a background in product strategy and software development, I bridge the gap between technical execution and business outcomes.

Working closely with the team on research and development around Agentic AI systems, LLM applications, and AI evaluation frameworks.

Contributing to shaping team projects, exploring how to design, test, and deploy AI systems that are reliable, scalable, and aligned with real-world use cases.

Focus areas include human-in-the-loop (HITL) approaches, improving model performance through structured evaluation, and building practical workflows for integrating AI into business and operational environments.

Collaborating with a multidisciplinary group to bridge the gap between cutting-edge research and applied AI solutions.

Developed enterprise microservices for aviation MRO operations, transforming manual maintenance workflows into digital solutions that improve operational efficiency and data quality.

Key Contributions:

• Built scalable microservices using Java, Spring Boot, and Quarkus for critical aviation maintenance systems

• Designed REST APIs and integrated enterprise systems via Kafka for real-time data processing

• Implemented automated workflows, PDF generation, and complex calculation engines from scratch

• Worked with Azure SQL, MongoDB, and Oracle databases to handle large-scale aviation data

• Delivered applications using CI/CD pipelines with Jenkins and OpenShift deployment

• Maintained high code quality through comprehensive testing (JUnit/Mockito) and SonarQube integration

**Technologies:** Java, Spring Boot, Quarkus, Microservices, Kafka, Azure SQL, MongoDB, REST APIs, Docker, OpenShift, Jenkins

Successfully delivered multiple mission-critical applications from concept to production, contributing to the digital transformation of aviation maintenance processes.

Spearheaded AI strategy development and product management initiatives, bridging technical AI capabilities with business value to drive enterprise AI adoption and implementation across various industries, including private equity and venture capital firms.

Key Contributions:

• Developed comprehensive AI strategies for enterprise applications, focusing on practical implementation and measurable business outcomes

• Designed and implemented RAG (Retrieval-Augmented Generation) systems for knowledge management and decision support

• Led prompt engineering initiatives to optimize AI model performance and user experience

• Built MCP (Model Context Protocol) servers to enhance AI system integration capabilities

• Conducted AI readiness assessments and created product roadmaps for AI-driven solutions

• Delivered specialized workshops and training sessions for PE/VC firms on generative AI implementation, demonstrating how to integrate AI into investment workflows, due diligence processes, and portfolio company operations

• Consulted with financial services firms on AI adoption strategies, focusing on deal sourcing, market analysis, and operational efficiency improvements

• Managed cross-functional AI projects from conception to deployment, ensuring alignment with business objectives

• Performed product testing and quality assurance for AI applications and generative AI solutions

Technical Leadership:

• Collaborated with engineering teams to integrate AI capabilities into existing systems

• Developed technical requirements and specifications for AI product development

• Conducted risk assessments and mitigation strategies for AI project implementations

Successfully positioned AI as a strategic business enabler while maintaining focus on practical implementation and user adoption across enterprise and financial services sectors.

Led comprehensive Java programming training programs, mentoring students from beginner to advanced levels while guiding them through complete application development lifecycles.

Key Contributions:

Designed and delivered structured Java curriculum covering core programming concepts, object-oriented programming, Spring Boot framework, and enterprise development practices

Provided personalized coaching and mentorship to students, adapting teaching methods to different learning styles and skill levels

Guided students through end-to-end project development, from initial concept and requirements gathering to final application deployment

Supervised capstone projects where students built complete web applications using Java, Spring Boot, databases, and modern development tools

Conducted interactive coding sessions, code reviews, and debugging workshops to reinforce best practices

Created practical exercises and real-world scenarios to bridge the gap between theoretical knowledge and industry requirements

Delivered technical presentations on software architecture, design patterns, and modern Java development methodologies

Mentored students in building portfolio-ready applications that demonstrate enterprise-level development skills

Facilitated collaborative learning environments and peer-to-peer knowledge sharing

Teaching Impact:

Successfully trained multiple cohorts of developers who progressed to junior and mid-level positions

Developed hands-on learning materials and project templates that enhanced student engagement and retention

Maintained high student satisfaction rates through personalized attention and practical, industry-relevant curriculum

Technologies: Java, Spring Boot, Object-Oriented Programming, Database Design, Git, Maven, RESTful APIs, Software Architecture

Empowered aspiring developers with both technical expertise and practical application development experience, preparing them for successful careers in software engineering.