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Samir Bajaj

Builder.
Entrepreneur.
Mentor.
Writer.
Perpetual Learner.
Wannabe Musician.

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Resumé

Samir Bajaj

http://samirbajaj.com

samir@samirbajaj.com

Career Summary

  • A hands-on, seasoned Technical Lead with a multidisciplinary skill set spanning Software Engineering, Machine Learning, and Distributed Systems.
  • Several years of industry experience in leading large and complex cross-domain projects across multiple teams and disparate business units.
  • Graduate and Professional degrees in Computer Science and Artificial Intelligence.
  • A pragmatic who is passionate about technology, learning new things, and helping others to work better and more effectively.

Specialties

Microservices, Scalable and Highly-Available Distributed Systems, Machine Learning, GenAI and Agentic Workflows, Natural Language Processing, Functional and Object-Oriented Programming.

Work Experience

2024—Present: Senior Principal Engineer, Machine Learning at Workday

2018—2024: Principal Engineer, Machine Learning at Workday

In addition to core product development and engineering, my responsibilities encompass hiring and mentoring, influencing the organization’s technical direction, and providing input for major initiatives.

Current and past projects include:

  • Design and implementation of AI safety guardrails in agentic workflows across the Workday platform.
  • Building MCP (Model Context Protocol) servers and clients to enable agentic workflows and natural language interfaces to APIs and resources for use internally as well as in production-ready tools and services.
  • A scalable and extensible feature store to address the model training and inferencing requirements of all ML projects across the organization.
  • A Retrieval-Augmented Generation (RAG) system using LLMs (Large Language Models) contextualized on proprietary, tenant-specific data to deliver unique value to enterprise customers.
  • Unlocking new business opportunities by exposing core ML functionality via APIs on the Workday platform.
  • A distributed, tenant-aware vector index for similarity search at scale, deployed as part of a high-throughput, low-latency recommender system.
  • A high-performance Document Understanding service that leverages Computer Vision (OCR) and NLP to extract, categorize, and validate data from a variety of business and legal documents.
  • A scalable, container-based platform that addresses all aspects of the Machine Learning workflow, from training and evaluation of model artifacts, to deployment, monitoring, and security.

2011—2017: Software Engineer, Siri at Apple

Led the design and development of several ML-based systems that power the virtual personal assistant.

  • Implemented new domains, ontologies, and request processing pipelines to expand Siri’s skill set.
  • Improved the NLP system by introducing statistical techniques in parsing and query understanding.
  • Launched Siri on new platforms: macOS, Apple tv, and HomePod.

2008—2011: Software Engineer, Kindle at Amazon

Responsible for the design and implementation of Web services, tools, and utilities to support Amazon's growing business in digital content, including music, movies, and Kindle ebooks. The systems processed hundreds of millions of transactions daily, pushing the limits of traditional data management and posing unique challenges in scalability and performance.

  • Designed the Digital Vendor Services workflow, enhancing scalability, reducing latency, and separating operational and reporting aspects of the system.
  • Built the Identity and Content Delivery systems for the Kindle E-reader.

2003—2008: Software Engineer, SQL Server at Microsoft

Contributed to the design and implementation of two Object-Relational Mapping technologies, LINQ to SQL as well as the Entity Framework, that shipped as part of the .NET runtime in SQL Server 2008.

1995—2003: Software Engineer, AutoCAD at Autodesk

Made significant and noteworthy contributions to six releases of the flagship product.

  • Designed and implemented APIs to allow third-parties to extend the AutoCAD platform.
  • Led the development of client-side Internet functionality, as well as support for Digital Signatures and Encryption across the product line.

Formal Education

  • Graduate Certificate in Artificial Intelligence, Stanford University.
  • M.Sc. in Computer Science, University of California, Riverside.

Technical Skills

  • Java, Scala, Python, JavaScript, SQL, C++, and related technologies
  • Scalable and Highly-Available Distributed systems
  • Integration with major cloud providers like AWS and GCP
  • Machine Learning, Natural Language Processing, LLMs and Generative AI, Agentic Systems

References

Available upon request. Some endorsements can be found on my LinkedIn page.