Nagaraj P.

* Took on a time-bound consulting mandate to advise leadership teams on AI adoption, platform scalability, and architecture modernisation. * Conducted deep architecture and product reviews to identify where AI/ML could deliver measurable business impact versus traditional systems. * Defined practical AI roadmaps covering data readiness, model strategy, and production deployment, aligned with near-term and long-term business goals. * Designed and validated cloud-native architectures for AI-enabled SaaS platforms with a focus on reliability, cost efficiency and maintainability. * Established MLOps and governance best practices to help teams move from experimentation to stable, production-grade AI systems. * Acted as a senior technical advisor and mentor, enabling internal teams to make better architectural and executions beyond the engagement.

Leading AI R&D strategy and driving projects from concept to deployment. Overseeing AI and ML model implementations, ensuring data integrity, and continuous improvement. Experienced in solving complex challenges with innovative AI solutions. Also, spearheading international product launches, aligning cross-functional teams, conducting market research, and developing tailored go-to-market strategies for successful execution.

o Led comprehensive product lifecycle for Alexa-enabled devices, driving global adoption in millions of homes. o Owned program governance by implementing frameworks for cross-org communication, risk escalation, and milestone tracking o Played a key role in shaping the organisations direction by actively contributing to the development of both the 3-Year Strategic Plan, Yearly Plan and Quarterly plan, defining high-impact goals at the organisational level. o Collaborated cross-functionally with engineering, product, and leadership to align on roadmaps, milestones, resource planning, and funding goals. o Adopted agile methodologies, accelerating product delivery cycles by 20%. o Translated complex AI capabilities into tangible business outcomes, increasing stakeholder engagement. o Managed cloud-native solutions on AWS leveraging S3, Lambda, Glue, and Kinesis for scalable data ingestion. o Managed cross-functional teams, delivering multiple AI projects simultaneously with high quality and timely execution. o Influenced executive stakeholders through technical reviews, roadmap planning, and operational briefings. o Drove the development of the Go-To-Market (GTM) strategy by aligning cross-functional teams on customer needs, product positioning, and launch timelines—resulting in faster time-to-market and improved customer adoption o Proactively addressed program ambiguities, leveraging strong problem-solving and negotiation skills to align the diverse stakeholders o Enabled faster decision-making through clear and consistent program reporting to executive leadership and technical teams. o Conducted structured performance management, including regular reviews and clear goal setting, significantly improving team productivity. o Directed a cross-functional team of engineers across backend, data engineering, and analytics verticals o Fostered a high-performance culture through consistent recognition, career progression support, and leadership coaching.

o Defined Master Data Management and ML/AI product strategy aligned with business goals, successfully deploying solutions impacting 200+ healthcare facilities in US region. o Built analytics platforms that processed 50M+ patient interaction data points, enabling provider-level operational insights and to improve the patient turnaround time. o Partnered with clinical operations and data governance teams to ensure HIPAA-compliant tool deployment across various regions in US. o Directed enterprise data lake buildout using Hadoop, Kafka, Spark, and Snowflake, supporting HIPAA-compliant data exchange. o Led a team of 20 Engineers across backend, DevOps and Project Managers; managing talent effectively through structured hiring, performance management, mentoring, and career development initiatives. o Led end-to-end data engineering solutions, significantly improving data quality and operational efficiency. o Executed complex programs end-to-end by de-risking delivery paths, aligning milestones, and managing cross-team dependencies o Optimized database architectures and enhanced ETL processes for superior data integration and reliability. o Streamlined product architecture to support scalable data ingestion and high-volume processing. o Managed data infrastructure costs effectively, ensuring resource allocation aligned with strategic priorities. o Conducted structured hiring and mentoring programs to build and sustain a high-performance engineering team.

o Led design and deployment of data ingestion platforms using Azure Data Factory, and Azure ML. o Executed the AI-driven renewable energy project reducing wind turbine downtime by 20%, significantly lowering maintenance costs. o Developed predictive analytics solutions, optimizing large-scale data ingestion and reliability for LAUSD. o Streamlined MLOps pipelines, achieving faster deployment and continuous model improvements on Azure AI. o Managed cross-functional agile teams to execute large-scale AI projects efficiently and effectively. o Built and maintained strategic relationships with key stakeholders, enhancing trust and collaborative success. o Fostered innovative culture within teams, driving continuous improvement and industry leadership. o Conducted robust talent acquisition processes, onboarding high-performing individuals into critical roles. o Implemented structured performance management and career progression frameworks, significantly enhancing employee satisfaction. o Provided regular mentorship, coaching, and feedback, driving sustained professional growth within the team.

o Developed data warehouse components and ETL pipelines to integrate Medicare and Medicaid healthcare related data at scale for US region. o Developed software applications focusing on robust code quality and efficient performance optimization. o Collaborated closely with cross-functional teams to ensure alignment between technical solutions and business requirements. o Executed thorough code reviews and implemented best practices to enhance software reliability. o Developed automated testing frameworks, significantly improving software quality and deployment efficiency.

o Developed robust Java based applications, contributing to successful project deliveries. o Managed code optimisation efforts, significantly improving application performance. o Performed comprehensive code reviews, ensuring high-quality software delivery. o Enhanced application scalability and reliability through strategic software design improvements. o Streamlined database interactions, improving application data processing efficiency.