Apr 2025 – Aug 2025 · 4 mos

• Leading a cross-functional squad of 8 engineers (Frontend, Backend, and AI engineer) in the AI team, overseeing quarterly roadmap planning and technical execution.
• Splitting my time as a hands-on AI Engineer, currently contributing to the development of the AI agents feature.

Jan 2024 – Mar 2025 · 1 yr 2 mos

• Developed and successfully delivered Sentiment Analysis Phase I, including modeling and generating key analytics reports, laying the foundation for ongoing customer-facing insights.
• Directed the development of a comprehensive suite of LLM-based Agent Co-Pilot features (Issue Summary, Suggested Response, and Smart Compose)
• Key contributor to the backend architecture guild at Helpshift to support critical cross-functional initiatives.
• Drove improvements in team efficiency and project delivery through direct mentoring of junior developers, leading sprint calls, and optimizing quarterly capacity planning for multiple AI features.

Mar 2022 – Dec 2023 · 1 yr 9 mos

• Led a project utilizing LLM-based RAG implementation to address common user queries efficiently.
• Developed a KNN-based recommendation feature, improving user intent determination for customer support.
• Analyzed performance metrics for the user intent classification service, enabling automated intent determination.
• Built an analytics pipeline to enhance ML Observability for existing ML services.
• Interviewed, onboarded, and mentored three junior engineers in the team.

Jan 2022 – Feb 2022 · 1 mo

• * Led mobile SDK delivery for Unity and Unreal Engine

Jan 2021 – Dec 2021 · 11 mos

• Delivered a major release for mobile SDK by leading business-critical projects like feedback bots and Unity VSP.
• Mitigated customer pain points during SDK integration, enhancing developer experience and satisfaction.

Oct 2019 – Dec 2020 · 1 yr 2 mos

• Optimized AWS spend, saving $2.5M annually through analytics and configuration improvements.
• Analyzed 1.4M fatal SDK logs using Pandas and NumPy to identify actionable tech tasks.

Jul 2018 – Dec 2018 · 5 mos · Pune, Maharashtra, India

• (Academic curriculum-integrated internship)
• Engineered an automated Python bug triage system utilizing multivariate analysis, cutting NVIDIA Capture SDK bug investigation time by approximately 26%.
• Developed a Python GUI tool for Event Tracing for Windows (ETW) log analysis to accelerate debugging workflows.

Oct 2017 – Nov 2017 · 1 mo · Remote

Jan 2017 – Feb 2017 · 1 mo · Remote

• (Internship under Prof. Sameer Mathur in Data Analytics & Applications)
• Proficient in data analysis and visualization, I've successfully applied data analytics concepts to solve real-world business challenges, including Harvard Business Review case studies and an airline industry project.