rugved_s_darwhekar // sys_status: operational

INITIALIZING_SESSION...

rugved_s_darwhekar

"Find why the queue is full, not just how to empty it faster."

INITIATE_CONNECTING → LINKEDIN ↗ GITHUB ↗

OPEN_TO: Solutions Engineering Technical Support Eng AI / DevEx Software Engineering

// DEPLOYMENT_HISTORY

operational logs // experience & impact

● ACTIVE

HCLTECH

(SUPPORTING GOOGLE)

OCT 2021 – PRESENT
4.5 YRS
SAN JOSE, CA

Technical Support & Solutions Engineer — Android · Generative AI · DevEx

Triaged 100+ complex OS and system UI bugs weekly via deep-dive root cause analysis (logcat, ADB, bugreports), maintaining a 0.7% bounce rate and 2% hop rate, the lowest on a 40-person team supporting Android on Pixel.
Designated as the team's dedicated engineer for C-suite executive escalations, a direct recognition of sustained triage accuracy, and leveraged that trust to establish and lead an L2 specialist group for thermal and battery regression triage.
Led a developer productivity initiative resolving SDK integration blockers across Python, Java, and Go, including authoring a canonical Gemini 2.0 Flash migration script that unblocked external developers.
Architected a RAG pipeline on Google Cloud (Vertex AI) using parent-child chunking, BM25 + dense vector hybrid search (RRF reranking), and Qdrant, evaluated against a golden dataset with RAGAS Faithfulness metrics, reducing developer feedback analysis time by 70%.
Engineered an automated ticket classification system (Python, Flask) achieving 85% routing accuracy with a Human-in-the-Loop (HITL) grace-fail threshold for low-confidence edge cases, reducing manual triage overhead and earning stakeholder buy-in for a dedicated AI tooling role.
Conducted build bisection on pre-release system crashes by toggling Android feature flags and diffing behavior across builds to isolate exact failing code paths, directly unblocking hardware release timelines.
Engineered Python scripts to process logcat and ADB streams, extracting high-signal Exception and Fatal blocks to accelerate root cause identification for unreleased hardware and OS builds.
Built and maintained a Hardware-in-the-Loop (HIL) automation framework for Android devices using Python and Appium, converting manual hardware validation into 100+ repeatable automated test flows.
Isolated a critical face-auth failure by writing a custom Android sample app to reproduce the exact issue, delivering engineering a fully reproducible test case that enabled an immediate patch.
Served as technical lead for junior engineers, establishing RCA best practices and debugging playbooks that improved team triage accuracy from 92% to 98%.

PythonVertex AIRAG QdrantFlaskAndroid SDK ADBAppiumGCPGemini

CITY OF LA

HOUSING DEPT

OCT 2020 – OCT 2021
LOS ANGELES, CA

Software Support Engineer — Web

Functional + regression testing for housing portal serving 3.6M residents.
Resolved 300+ bugs — brought platform to WCAG 2.1 and Section 508 compliance.
Integrated automated smoke checks into CI pipeline, reducing post-deploy emergency fixes.

JavaJavaScriptC# ASP.NETCI/CDWCAG

VISION LABS

MAY – OCT 2020
SAN FRANCISCO, CA

Android Developer

Built cross-platform VR apps integrating BLE and Wi-Fi P2P.
Automated critical user journeys via Appium + Firebase Crashlytics.

KotlinAndroidBLEAppiumFirebase

EDUCATIONAL_NODE

MS COMPUTER SCIENCE

Cal State Northridge

GPA: 3.64

KEY MODULES

Data_OpsSystem Design ML FundamentalsDistributed Systems

// SYSTEM_INVENTORY

system_inventory // stack & capabilities

AI / ML

Vertex AI / GCP

RAG / LangChain

Gemini / LLMs

Qdrant / Embeddings

Prompt Engineering

CORE PROGRAMMING

Python

Java

Kotlin

JavaScript / Node

SQL

MOBILE & TOOLING

Android SDK / ADBExpert

Logcat / BugreportsExpert

Appium / HILAdvanced

REST API / PostmanAdvanced

Flask / DjangoAdvanced

FRAMEWORKS & ENGINES

n8n / Agentic AIAdvanced

Git / GitHubExpert

JIRA / AgileExpert

ReactIntermediate

FirebaseAdvanced

// ACTIVE_CREDENTIALS

Google: Generative AI Fundamentals

Google: Intro to Generative AI

AWS Partner: Generative AI Essentials

Android Development: UI with Kotlin

// ROOT_CAUSE_EXCELLENCE

neural_pipelines // featured work

AI Infrastructure

Enterprise RAG Pipeline

● PROD

THE PROBLEM

Developer feedback was drowning in unstructured noise. Built a production RAG system on GCP to surface signal fast — evaluated with RAGAS Faithfulness metrics.

70%

Reduction in
feedback analysis time

Vertex AIQdrantBM25+DenseRRFRAGAS

PARENT-CHILD CHUNKING · HYBRID SEARCH

AI Tooling

Ticket Classifier + HITL

● ACTIVE

THE PROBLEM

Manual triage was slow and scaled to zero. Built a classifier with Human-in-the-Loop fallback so edge cases never slip and stakeholders stay in control.

85%

Automated routing
accuracy

PythonFlaskHITLML Classification

GRACE-FAIL THRESHOLD · LOW-CONFIDENCE ROUTING

Test Automation

Android HIL Framework

● ACTIVE

THE PROBLEM

Pre-release hardware validation was entirely manual and unrepeatable. Built an HIL framework running real device tests — directly unblocked hardware release timelines.

100+

Repeatable automated
test flows on real HW

PythonAppiumADBAndroid SDK

VIEW GITHUB ↗

// OPEN_SOURCE_MODULES

Reddit Beta Analyzer

LangChain · Gemini · Reddit API

Board Games FAQ (RAG)

LLM · RAG · Python

BiometricAuth

Kotlin · Fingerprint · Face Unlock

Android Tester