AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Staff Software Engineer at Uber building production agents | LangGraph, MCP, Cadence, LLM evals | 15+ yrs distributed systems
Building production agents and foundational distributed systems at Uber. Right now, I lead agentic architectures for Uber for Business (U4B), having previously built the core platform foundations for Uber Eats Merchants. What I do in practice: ▪ Unified Agentic Architecture: Building an "army of agents" routing intents across specialized sub-agents (Setup, Spend Analyzer, Support). Balancing probabilistic LLM behavior with deterministic fast-path routing leveraging super memory/context store to bypass the LLM whenever a faster, cheaper path exists. ▪ Durable State & Migrations: Leading complex runtime transitions (e.g., migrating core flows to LangFx) with resilient fallbacks to guarantee zero context loss. ▪ Production Eval Frameworks: Building automated offline/online evaluation harnesses handling multi-turn, voice, and text agents across 10+ languages using golden datasets to catch silent regressions. ▪ Core Platform Scale: Leading building and scaling key systems, from realtime analytics platforms to multi-tenant merchant store-hierarchies. Stack: LangChain, LangGraph, LangFx, Claude Code, Cursor, MCP/LLM gateways, Cadence, Kafka, Python, OpenSearch, Redis, Go, Java. Pre-GenAI Journey: 15+ years of experience building high-throughput distributed architectures at Uber, Dunzo, Noodle.ai, Goldman Sachs, and Morgan Stanley. Always happy to chat about: Shipping agents that actually survive real-world traffic, balancing deterministic vs. probabilistic routing, building eval frameworks that don't rot, self-improving services, long-running agent loops, agent super memory, and scaling business-critical data hierarchies.
Indian Institute of Technology, Delhi
Master of Computer Applications / M.Tech, Computer Science
January 1, 2006 – January 1, 2008
Jawaharlal Nehru Technological University
BTech, computer sci
January 1, 2002 – January 1, 2006
Uber
Staff Software Engineer
December 1, 2019 – Present
Bengaluru, Karnataka, India
CNCF [Cloud Native Computing Foundation]
TOC Contributor
November 1, 2019 – Present
Dunzo
Senior Technical Architect
October 1, 2018 – December 1, 2019
Karnataka, India
Noodle.ai
Principle AI Engineer / Architect
June 1, 2017 – December 1, 2019
Bengaluru, Karnataka, India
Spire.AI Copilot for Talent
Architect
March 1, 2017 – June 1, 2017
Spire.AI Copilot for Talent
Senior Principal Engineer
October 1, 2015 – June 1, 2017
Spire.AI Copilot for Talent
Principal Software Engineer
October 1, 2014 – June 1, 2017
Goldman Sachs
Senior Software Engineer
September 1, 2012 – August 1, 2014
Bangalore
Morgan Stanley
Manager
August 1, 2008 – August 1, 2012
Mumbai Area, India
gRPC [Golang] Master Class: Build Modern API & Microservices
Udemy
June 24, 2026 – Present
Go: The Complete Developer's Guide (Golang)
Udemy
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Generative AI with Large Language Models
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a long and varied career history across multiple companies, including large corporations (Uber, Goldman Sachs, Morgan Stanley) and AI-focused startups (Noodle.ai, Spire.AI). This suggests adaptability to different organizational cultures. The role as a TOC Contributor at CNCF indicates community involvement and a collaborative mindset. However, the target role of 'Data Analyst' is a significant shift from their extensive 'Software Engineer' and 'Architect' background, which might indicate a potential mismatch in expectations or a need for re-skilling in core data analysis techniques. The candidate's experience is heavily skewed towards engineering and AI/ML system design rather than pure data analysis, which could be a cultural fit challenge for a dedicated data analyst team.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in complex projects (e.g., BEAST, Data Cartridge platform) and empowering teams, suggesting strong operational fit for roles requiring technical leadership and collaboration. The description of optimizing inventory allocation and reducing demand-supply mismatches indicates a results-oriented approach. However, without specific project details or interview data, soft skills like communication style, conflict resolution, or adaptability cannot be fully assessed.