72%AI Ticket Auto-Resolution
1.2sMedian Support Response Time
−30%API Latency Reduction
95%ETL Data Accuracy
−80%Manual QA Eliminated
+40%Portal Adoption
99.7%System Uptime (90d)
7+Years Production Engineering
72%AI Ticket Auto-Resolution
1.2sMedian Support Response Time
−30%API Latency Reduction
95%ETL Data Accuracy
−80%Manual QA Eliminated
+40%Portal Adoption
99.7%System Uptime (90d)
7+Years Production Engineering
Senior Full-Stack · MCP Agents · RAG Pipelines · AI Systems

KartikeyGupta

7 years building production AI infrastructure — MCP agents, RAG pipelines, distributed backends, and full-stack systems that ship at scale.

Resume
7+
Years Production
72%
AI Auto-Resolution
−30%
API Latency
95%
ETL Accuracy
Selected Work

Systems Built

Six production systems — each with a distinct constraint, a deliberate architecture, and a measurable outcome.

support.evren.app / dashboard
RESOLVED TODAY347AI HANDLED38%AVG RESPONSE1.4sQUEUE12RECENT TICKETSLogin error on mobile appAIPayment declined — card validHumanBulk export timeoutAIAccount merge requestPendingLLM ACTIVITY● Classify intent● Draft response● Escalation check● Send & log● Waiting…LIVE
01 / 06LiveEvren

AI-Powered Customer Support Platform

AI support platform on Groq Llama 3.3 — auto-resolves 72% of tier-1 tickets without human intervention, and extends to agentic workflows: scheduling, support booking, guided multi-step flows. 99.7% uptime over a 90-day window.

72% tier-1 auto-resolution without human intervention3 agentic workflow types99.7% uptime
Groq APILlama 3.3OllamaNode.jsReactMySQLRedisDocker
Read Case Study
agents.evren.internal / workflow-engine
TRIGGERSchedule / APIFETCHDB QueryPLANLLM ReasoningEXECUTEMCP ToolsNOTIFYSlack / EmailLOGAudit TrailWORKFLOW RUNNINGrun_id: wf_7f2a91c · 0.8s
02 / 06LiveEvren

MCP-Based AI Agent Workflow Engine

MCP server exposing internal read endpoints as typed tools for AI agents. Extended via Groq Llama 3.3 agentic layer to execute actions: appointment scheduling, support call booking, and guided multi-step flows — all with immutable audit trails.

3 agentic workflow types automated~6h/week reclaimed100% audit coverage
MCP ProtocolGroq APILlama 3.3Node.jsMySQLDockerAWS Lambda
Read Case Study
portal.evren.app / admin
ADMIN & SUPPORT PORTALSYSTEMS ONLINE47OPEN TICKETS12API LATENCY−30%YOUR ROLESuper Adminfull accessOS MANAGEMENTPersonal — MacBook ProOnlineTeam Alpha — 8 systemsAll upTeam Beta — 12 systemsAll upTeam Gamma — 14 systems1 alertSUPPORT PORTAL — INTERNALVPN config issue — Team AlphaOpenLog analysis — latency spikeDoneAccess request — Viewer roleReviewSystem patch — Team GammaOpen
03 / 06LiveEvren

Admin & Support Portal

Customer-facing Admin Portal for enterprise OS management (V2 rebuild from scratch) + internal Support Portal. Migrated Python → Node.js, designed 4-tier RBAC, rebuilt React UI — delivered −30% API latency, +40% adoption, −50% debug time, zero downtime.

−30% API latency+40% portal adoption−50% debug time
Node.jsReactPythonMySQLRedisRBACDocker
Read Case Study
bestpeers.io / web · mobile · smartwatch
UNIFIED PLATFORM — 3 SURFACES, 1 BACKENDWEB APP+25%MOBILEWATCH98bpmSHARED BACKENDNode.js APIPythonMySQL DBShared State−35% bug rate+25% performance
Cross-Platform Sync Architecture
REACTWEBRN MOBILENODE.JSGATEWAYPythonMYSQL DBWATCHBRIDGE
04 / 06ShippedBestpeers

Cross-Platform Healthcare Monitoring Platform

Unified healthcare monitoring platform across a custom smartwatch (HR, SpO2, GPS), React Native mobile, and web dashboard — all on one Node.js backend with one auth contract. Led a 3-engineer team. +25% performance, −35% bugs.

+25% performance−35% bug reports1 backend, 3 surfaces
React.jsReact NativeNode.jsMySQLJWT Auth
Read Case Study
internal.worldpay.com / etl-monitor
ETL PIPELINE · LIVE STATUSEXTRACTSQL Server● ActiveVALIDATESchema check● ActiveTRANSFORMField mapping● ActiveLOADSalesforce CRM● ActiveVERIFY95% accuracy● DoneRECORDS TODAY84,291ACCURACY95.0%ERRORS0LAST SYNC14s[09:41:02] SYNC COMPLETE · 1,204 records pushed to Salesforce[09:41:01] Transform: null fields defaulted · 3 rows patched[09:40:58] Validation passed · schema v2.4[09:40:55] Extract: 1,204 rows from orders_delta
05 / 06ProductionFIS Global

Fault-Tolerant ETL Sync Pipeline

Bidirectional ETL sync between MongoDB and Salesforce CRM — built with SSIS. Schema validation, dead-letter queuing, exponential backoff retry, and an immutable PostgreSQL audit trail. Eliminated weekly manual reconciliation entirely.

95% data accuracy−80% manual QAZero manual reconciliation
SSISMongoDBSalesforce APIPostgreSQL
Read Case Study
fis.internal / test-runner
TEST SUITE90%+ coverageSELENIUMChrome / FirefoxAPI RUNNERREST assertionsCOLLECTResults + logsCI REPORTPass / fail / coverage
06 / 06ProductionFIS Global

Selenium WebDriver Automation Framework

End-to-end CRM regression automation framework built with Selenium WebDriver. 90%+ CRM workflow coverage — every major user journey automated. Eliminated manual regression testing, runs the full suite on every CI push in under 8 minutes.

90%+ CRM workflow coverage−80% manual QA<8 min full CI runtime
Selenium WebDriverPythonMavenPytestCI/CDPage Object Model
Read Case Study
Freelance & Side Projects

Client work and independent builds shipped outside of full-time roles.

Lex & Ledger

Legal & financial services marketplace connecting users with verified lawyers and CAs — booking system, WhatsApp notifications, multi-role auth (User / Expert / Admin), AI document processing.

ReactNode.jsMongoDBGroq AIJWTAWS S3
Livoh.in

Full-stack home decor e-commerce platform — OTP auth, product catalog, cart & checkout, shipping integration, and automated GST invoice generation.

ReactTypeScriptExpressPrismaPostgreSQLAWS S3
Sunpress Organic

Manufacturing P&L and costing tool for edible oil production — tracks raw seed input, oil/khari yield, overhead allocation, and per-unit profitability across pack sizes.

ReactNode.jsPostgreSQL
PlotSync

Real estate plot management app for tier-3 Indian cities — prevents double-booking conflicts and provides real-time plot availability visibility for developers and sales teams.

React NativeNode.jsMongoDB
Experience

Where I've shipped.

Three companies, six years, measurable outcomes at every step.

Jan 2023 – Present
Evren
Senior Full-Stack Developer
Built and scaled an AI-first admin and support platform from scratch
+40% Portal Adoption−30% API Latency72% AI Auto-Resolution
  • Led Python → Node.js backend migration, improving throughput and maintainability across the platform
  • Built AI support chatbot on Groq Llama 3.3 with streaming completions — 72% of tier-1 tickets auto-resolved without human intervention
  • Designed MCP server exposing internal APIs as typed tools; extended to agentic workflows — appointment scheduling, support call booking, guided multi-step flows
  • Implemented 4-tier RBAC and rebuilt the customer-facing Admin Portal (V2) from scratch; query optimization cut API response times by 30%
Node.jsReactPythonMySQLGroqLlama 3.3MCPDockerAWS
Jul 2021 – Dec 2022
Bestpeers Infosystem
Full-Stack Developer & Team Lead
Led a 3-engineer team shipping web, mobile, and smartwatch app on a shared backend
+25% Performance−35% Bug ReportsTeam Lead · 3 Devs
  • Built unified product across React.js web, React Native iOS, and a custom smartwatch with a single Node.js backend and shared JWT auth contract
  • Enforced structured code review gates and architecture standards — 35% reduction in bug reports directly attributed to this process
  • Resolved memory leaks, N+1 queries, and security vulnerabilities during development, not after ship
  • Applied Redux, Context API, custom hooks, and memoization for performant, scalable frontend architecture
React.jsReact NativeNode.jsReduxMySQLMongoDB
Aug 2019 – Jun 2021
FIS Global (Worldpay)
Software Developer
Built automation and data infrastructure handling financial-scale transaction data
90%+ Workflow Coverage95% ETL Accuracy−80% Manual QA
  • Built Selenium WebDriver CRM regression framework — 90%+ user-workflow coverage, eliminating 80% of manual QA effort
  • Developed fault-tolerant ETL pipeline bidirectionally syncing MongoDB with Salesforce CRM via SSIS — 95% data accuracy, zero manual reconciliation
  • Optimized complex SQL queries reducing report generation latency significantly on financial-scale datasets
  • Integrated CI/CD pipeline running the full regression suite in under 8 minutes on every deployment
PythonSeleniumSSISMongoDBSalesforce APIMavenCI/CD
Testimonials

From the people I've shipped with.

Kartikey played a key role in building and improving the UI using React.js, consistently delivering clean, responsive, and user-friendly interfaces. He has a strong understanding of component-based architecture and pays close attention to performance and usability. Alongside frontend work, he is well-versed in Node.js and contributed effectively to backend integrations, APIs, and business logic. Kartikey's ability to work across the stack makes him a reliable and versatile engineer.

Rajeev Sarathe
Python Engineer
Teammate@ Evren
LinkedIn

He is proactive, takes initiative, and consistently delivers high-quality work across both frontend and backend. Kartikey communicates clearly and works well with others, making collaboration smooth in a fast-paced environment. He takes ownership of his work and is reliable when it comes to execution and follow-through.

John Kevin Go
Software Engineering Manager
Direct Manager@ Evren
LinkedIn
Engineering Philosophy

How I approach the work.

Six principles that shape every system I build — accumulated over six years of production engineering.

Iteration
Ship to learn, not to plan

A working system in production teaches more in one week than six weeks of design docs. I bias toward getting something real in front of users, then improving it fast.

Ownership
Own the full stack

I don't hand off to "the frontend team" or wait on "the infra team." End-to-end ownership means I debug across the entire system and ship without blockers.

AI-native
AI as infrastructure, not a feature

The most durable AI integrations are invisible — woven into the workflow, not bolted on as a chatbot. I design LLM layers as reliable infrastructure with fallbacks, auditing, and graceful degradation.

Clarity
Readable systems over clever ones

Code that reads clearly is cheaper to maintain, faster to debug, and easier to hand off. I write for the engineer who comes after me, because that engineer is often me.

Product
Performance is a product decision

Every 100ms matters. Query optimization, caching strategy, and bundle size are product decisions, not engineering afterthoughts. I track them from day one.

Observability
Observability from the start

Structured logging, meaningful error messages, and audit trails are built in, not retrofitted. You cannot fix what you cannot see, and you cannot see what you did not instrument.

Stack

The full stack, front to back.

Five layers I own end-to-end. Every tool here is battle-tested in production.

AI & LLMs
Agents · Pipelines · Protocols
Groq APILlama 3.3Claude APIOllamaMCP ProtocolRAG PipelinesAI AgentsLangChainPrompt Engineering
Backend
APIs · Services · Infrastructure
Node.jsPythonExpress.jsREST APIsSystem DesignMicroservicesMessage QueuesGraphQL
Frontend
Web · Mobile · Cross-platform
React.jsNext.jsTypeScriptReact NativeTailwindFramer Motion
Data
Databases · Pipelines · Caching
PostgreSQLMySQLMongoDBRedisSSISSQL OptimizationETL Pipelines
DevOps & Cloud
AWS · Docker · CI/CD
AWS (EC2, S3, Lambda)DockerGitCI/CDNginx
About

The engineer behind the work.

I started writing production code at FIS Global in 2019 — building automation frameworks and ETL pipelines that handled financial-scale data at an enterprise with zero tolerance for error. That early constraint shaped how I think: instrument everything, fail gracefully, ship with confidence.

At Bestpeers, I led a 3-engineer team shipping a healthcare monitoring platform across React web, React Native mobile, and a custom smartwatch tracking heart rate, SpO2, and GPS — all from a single Node.js backend. I learned that clean architecture isn't aesthetic, it's operational: it's what lets you ship three surfaces without tripling the maintenance burden.

At Evren, I own the technical architecture — an AI support chatbot on Groq Llama 3.3, MCP agents, agentic workflows, and the customer-facing Admin Portal for enterprise OS management. I set technical direction, lead cross-functional engineering decisions, and mentor developers through code reviews and system design. The AI here is invisible infrastructure, not a UI feature bolted on.

github.com/kartikeygupta8
Kartikey Gupta
Quick Facts
RoleSenior Full-Stack & GenAI Engineer
Experience7 Years
EducationB.E. Computer Science
UniversityLNCT — RGPV
Graduated2019
Based inIndia (UTC+5:30)
StatusOpen to remote roles
Certifications
MongoDB Developer Certification
MongoDB, Inc. · 2021
Writing

Engineering in the open.

All posts
Contact

Let's build something real.

Open to full-time remote roles, contract work, and conversations about hard technical problems. If you need someone who ships production AI systems end-to-end — let's talk.

Replies within 24h.
kartikeygupta8@gmail.com·LinkedIn ↗·Resume
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