About
I build AI-native systems that turn research, data, and software engineering into practical products. With 10 years of experience across software engineering and intelligent systems, including 6 years focused on machine learning and AI, my work sits at the intersection of applied research, product thinking, and scalable architecture. I care about building systems that are useful, trustworthy, and designed to move from prototype to real-world impact.
AI · Systems · Product
My journey has been marked by a passion for deep-diving into tech from Machine learning, full stack, to IoT embedded system development, while embracing the philosophy of language-agnostic programming.
- Location: Boston, United States
- Email: yogesharjun94@gmail.com
I have gone from building traditional software to building systems that reason, retrieve, evaluate, and adapt. The part I care about most is making those systems useful in the real world, as part of the messy social fabric people already work and live in.
Skills
Resume
Over the years, I have had interesting opportunities to work on. From working for a Casino gaming company to building AI on Edge at Amazon Robotics, and then advancing applied AI research and data science at Harvard Business School, my career has been a whirlwind of technological experience. I have had a chance to do various full stack engineering, production deployments, data pipeline building, cloud ecosystem architecture, program management, mentorship and tech business consultancy. Here is my Professional Resume.
Professional Experience
Senior Machine Learning Data Engineer
Western Technology Alliance · Full-time | Boston, MA · Remote
Mar 2025 - Present · 1 yr 2 mos
- Architected enterprise AI roadmaps across LLM applications, edge ML, and data platforms, turning open-ended business needs into deployable technical programs.
- Led solution design for mission-critical enterprise and government environments, aligning stakeholders on security, governance, architecture, and delivery milestones.
- Deployed AI workspaces that combine deterministic multi-agent systems, harness engineering, and workflow automation to transform operational knowledge into repeatable organizational intelligence.
- Partnered with product, engineering, and stakeholder teams to convert AI proofs of concept into reusable delivery patterns, scalable platform blueprints, and production-ready execution plans.
Senior Machine Learning Data Engineer
Harvard Business School AI Institute · Contract | Boston, MA · On-site
Mar 2025 - Present · 1 yr 2 mos
- Led senior engineering for Vaiv , shaping the system architecture for a real-time AI business problem solver with voice, text, expert reasoning, durable memory, and grounded research artifacts.
- Architected the core intelligence service that centralizes model routing, context orchestration, retrieval, enrichment, and reporting behind clean internal APIs, giving product teams a reusable foundation for AI features.
- Designed a two-stage parent-child RAG retrieval system that indexes documents as focused evidence chunks linked to larger source sections, retrieves the most relevant evidence first, then reattaches full context for stronger citations, traceability, and lower hallucination risk.
- Built an accessible CLI layer on top of the RAG pipeline, giving engineers a simple way to ingest documents, run smart chunking and retrieval, inspect collections, and debug knowledge quality.
- Built an agentic evaluation harness for AI sessions using LLM-as-judge design patterns, plus an observability UI that scores transcripts across quality dimensions, flags human-review cases, and tracks drift over time.
- Automated external learner onboarding with an event-driven serverless workflow, replacing manual enrollment steps with structured extraction, account provisioning, and group assignment.
Machine Learning Data Engineer
Harvard Business School AI Institute · Full-time | Boston, MA · Hybrid
Jun 2024 - Mar 2025 · 10 mos
- Built agentic AI workflows that connected Amazon Bedrock, RAG, LLM orchestration, and cloud data services into production-facing research systems for applied AI experiments.
- Operationalized reusable AI components for experiments, evaluations, and application features, reducing the gap between research prototypes and deployable systems.
- Partnered with researchers and technical stakeholders to translate ambiguous AI ideas into maintainable services, repeatable engineering patterns, and measurable product outcomes.
Software Development Engineer
Amazon Fulfillment Technologies & Robotics · Contract | Boston, MA
Mar 2024 - May 2024 · 3 mos
- Engineered software for fulfillment and robotics systems with a focus on edge computing and machine learning, supporting applied automation in operational environments.
- Supported development of applied ML capabilities for robotics-oriented operational environments, helping move models closer to real-world fulfillment workflows.
- Collaborated on engineering tasks across distributed systems, automation, and machine learning infrastructure to improve reliability across robotics workloads.
Information Technology Scientist
Harvard Business School AI Institute · Full-time | Cambridge, MA
Jan 2023 - Mar 2024 · 1 yr 3 mos
- Architected and delivered an AWS data platform for the institute, aligning cloud storage, access control, and scalable analytics foundations.
- Led ETL migration from legacy systems to AWS, moving research data into queryable cloud stores and data catalogs.
- Standardized Git and programming practices across data science teams, turning ad hoc research code into repeatable engineering workflows.
- Built and productionized an end-to-end RAG-based Generative AI chat application in 10 days, spanning retrieval, LLM inference, application logic, and deployment for a rapid research use case.
- Developed a distributed Generative AI simulation pipeline for idea generation and prompt evaluation across GPT-4, Claude, and Llama 2, enabling scalable comparison of model outputs.
- Led a team in devising a self-instruct domain LLM fine-tuning and distillation approach using RAG and QLoRA to support domain adaptation.
- Designed AWS architecture for a Generative AI application with a containerized web app, serverless LLM inference, vector/NoSQL storage, and modular backend services to support scalable deployment.
Research Assistant and Program Manager
IoT Open innovation labs @Northeastern University | Boston, MA
July 2021 - December 2022 · 1 yr 6 mos
- Led development of a dynamic job marketplace platform using FastAPI, SQLAlchemy, Docker on AWS, GitHub Actions, Vue.js, and Vuetify, delivering both backend services and a usable research frontend.
- Architected a cloud solution and engineered an analytics engine for the platform with unstructured data store and live data pipelines, combining custom clickstream data, Google Analytics, and Microsoft Clarity for research insights.
- Designed and built an A/B-test research experiment platform, creating scalable architecture for efficient and accurate experimental testing under an ambitious timeline.
- Led a team of four with a clear work breakdown structure, agile milestones, and event-driven monitoring, improving project visibility and team responsiveness.
Software Development Engineer Coop
Amazon Robotics | Boston, MA
January 2022 - June 2022 · 6 mos
- Developed automation for robotic operation simulations, making existing services programmatically accessible and reducing manual simulation permutation runtime by 75%.
- Designed a machine learning optimizer based on finite difference gradient descent to generate optimal parameters and configurations for warehouse floor planning.
- Engineered a sidecar service within AWS Batch, redesigning the containerized runtime into a more automated and efficient cloud execution environment.
Senior Software Engineer
Kloudone | Chennai, India
October 2019 - December 2020 · 1 yr 3 mos
- Led 10 engineers and trained 30 engineering trainees, managing delivery, resource allocation, user stories, and coding standards that became part of application development across the organization.
- Implemented a SaaS application using React.js, Gatsby, and Flutter for iOS and Android, delivering full-stack, cross-platform features with analytics integration.
- Led a product design sprint and authored the product requirements and roadmap, aligning engineering delivery with market needs and organizational goals.
- Orchestrated Google Cloud infrastructure, server runtime, SSL certificates, application deployment, and ELK-based monitoring to improve cloud operations and observability.
Software Engineer
Freelancer | Chennai, India
December 2017 - October 2019 · 1 yr 11 mos
- Worked with external stakeholders to define scope and roadmap, then delivered a website and companion mobile app using Figma, Angular, LAMP, Flutter, and PHP scheduling services.
- Managed a team of five engineers and architected a MEAN stack progressive web application using Angular 8, TypeScript, Angular Universal, NgRx, RxJS, Express.js, and Sails.js.
Associate Software Engineer
Scientific Games | Chennai, India
June 2016 - November 2017 · 1 yr 6 mos
- Structured desktop application software using the open-source Chromium engine, enabling a browser-based product experience in a desktop runtime.
- Engineered backend services with .NET ASP MVC, MS SQL Server, and IIS to support casino gaming application workflows.
- Collaborated on web frontends using .NET Razor, Angular 1.x, d3.js, and jQuery, building a CSS3 animation library and reusable Angular data table template for cross-organizational use.
Research Work
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality
2026
Acknowledged for research assistance in the Organization Science article by Dell'Acqua et al. Published in Organization Science.
AI-Enabled Job Markets & Market Participation: A Field Experiment on how AI Shapes Jobseekers' Expectations of Competition
2025
Acknowledged for research assistance in the working paper by Sarah Bana and Kevin Boudreau. Available on SSRN.
TATA Consultancy Service Best Project
2016
On device IoT smart assistant using Natural language processing and Smart Fidelity with Speech Recognition on a Raspberry Pi.
Health Monitoring Systems by Prognotive Computing using Big Data Analytics
2015
A computing system that does prognosis with machine learning and soft computing techniques. Published in Procedia Computer Science.