Vetted SQL Professionals

“Data/analytics professional with experience across manufacturing and enterprise environments (Wisconsin School of Business project with CNH Industrial; roles/projects at Ascensia Technologies, S&C, and Adobe). Has hands-on work combining warranty/lifecycle tables with technician free-text notes using TF-IDF + tree models (XGBoost/Random Forest), and deep experience in entity resolution/reconciliation across mismatched financial systems using Python/SQL and fuzzy matching, with production-grade pipeline practices in Azure Data Factory/Databricks.”

“ML/NLP practitioner working across healthcare and business/finance use cases: currently fine-tuning a domain-specific Llama 3.1 model for safe reasoning over EHRs/clinical notes using RAG + RL/DPO and RAGAS-based evaluation. Has built UMLS-driven entity normalization pipelines with quantified quality gains and developed embedding/vector-DB systems (FAISS) for semantic matching and forecasting/recommendation applications at Aurora AI and Banxico.”

“Full-stack AI/LLM engineer who has deployed a production LLM backend (Mistral 14B) on GKE to auto-transform datasets and generate runnable ML training pipelines, addressing hallucinations, schema mismatch, latency, and burst scaling with caching/prompt compression and HPA. Also has internship experience (Splunk, BlackOffer) delivering data automation and 10+ Power BI dashboards for non-technical stakeholders with measurable efficiency gains.”

“Backend-leaning full-stack engineer with e-commerce and analytics experience who modernized synchronous order workflows into a Kafka-based event-driven architecture (Java/Spring Boot) to reduce checkout latency and peak-traffic failures. Has built production FastAPI services with JWT/RBAC and strong testing/observability, delivered React+TypeScript reporting dashboards, and handled AWS scaling incidents end-to-end (RDS read latency mitigated with read replicas and query tuning).”

“Full-stack engineer with Cisco supply-chain and Wipro internal platform experience, focused on customer-facing UI performance and secure backend services. Built a bulk Excel inventory upload feature (Spring Boot/Apache POI) that cut manual effort ~80%, and delivered high-scale Angular/React dashboards with strong reliability/observability (FastAPI, JWT, Docker, AWS, AppDynamics).”

“QA professional with ~7 years of experience working in Scrum teams, involved from requirements and user story creation through test strategy/planning, execution, defect triage in Jira, and verification. Highlighted catching multiple issues early on an AI-driven project to avoid production regressions and escalating a blocker where a frequently used UI was broken to get it fixed quickly. Has not shipped an AAA game title.”

“AppSec-focused customer advisor with hands-on experience integrating SAST/DAST/SCA into production CI/CD (Azure DevOps) and designing secure agent/scanning deployments in AWS (least-privilege IAM, private subnets, VPC endpoints). Demonstrates strong incident troubleshooting using logs/metrics/traces to diagnose load-related failures (timeouts/retry storms) and drive durable fixes, while tailoring risk/tradeoff communication across engineering, security, and leadership stakeholders.”

“Customer-facing technical support/solutions professional with experience at Stripe and Intuit helping developers take payment API and webhook integrations from testing to production. Uses Datadog and AWS CloudWatch to diagnose real-time production issues (e.g., webhook signature validation errors causing retries/delays) and unblocks customer deployments through hands-on, developer-oriented guidance.”

“Full-stack engineer building real-time internal banking operations dashboards (Java/Spring Boot microservices + React/TypeScript) with Kafka-based streaming and post-launch performance optimizations. Also shipped a production internal AI support assistant using RAG (Confluence/PDF/support docs ingestion, embeddings + vector DB retrieval) with guardrails, evaluation loops, and observability to reduce hallucinations and prevent regressions.”

Alex ZhuZhou

Screened

Intern Full-Stack Software Engineer specializing in AI/LLM platforms and data systems

Berkeley, CA2y exp

“Backend/LLM engineer with experience productionizing RAG systems (legal-case natural language querying) and optimizing for latency/cost, including a reported ~40% reduction via Redis caching and batching. Built monitoring and real-time debugging workflows (FastAPI, structured logging, correlation IDs, sandbox repro) and regularly delivered technical demos/workshops. Also partners with BD/sales to translate LLM capabilities into business value, including ESG-metric extraction from corporate filings.”

Alexander Taylor

Screened

Principal Automation & Robotics Engineer specializing in lab automation deployments

San Diego, CA4y exp

“Lab automation engineer building an automated weighing robot system for Lilly’s analytical chemistry group, integrating a 6-axis Mecademic robot, Mettler Toledo balance, and vision/barcode verification with safety protocols for live lab operation. Experienced in production Python for instrument control, data processing, and CV/ML, including authenticated Data Lake API integrations with fault handling. Also improved automated sample storage throughput 2–3x via pick-order optimization and partners closely with scientists to deliver MVP-to-production experimental automation workflows.”

Akhil Jaggari

Screened

Mid-level Full-Stack Software Engineer specializing in scalable web platforms and cloud microservices

CA, CA6y exp

“Backend engineer with fintech/real-estate lending domain experience (Berkadia) building Python/Flask services for indicative loan pricing across Fannie/Freddie workflows. Strong in scalable AWS architectures (S3, Lambda, SageMaker), database performance (PostgreSQL read replicas, indexing, pooling), and high-throughput optimizations (streaming exports, Redis caching) with measurable production impact.”

Vamshikrishna Bandi

Screened

Senior AI/ML Engineer specializing in Generative AI and agentic multi-agent systems

6y exp

“Built and shipped a production LLM-powered multi-agent RAG system to automate complex internal support workflows, integrating tool execution (SQL/APIs) with validation guardrails to reduce hallucinations. Optimized for real-world latency and cost via model routing, caching, and async parallel tool calls, and enforced reliability with CI-gated golden test sets derived from anonymized production queries.”

Praveen Nutulapati

Screened

Mid-level Generative AI Engineer specializing in LLM fine-tuning, RAG, and agentic systems

New York, NY6y exp

“Built and deployed a production multi-agent RAG system at JPMorgan Chase to automate regulated credit analysis and compliance clause discovery across large internal policy/document libraries. Implemented LangGraph-based supervisor orchestration with structured state management (Azure OpenAI) to support long-running, resumable workflows, plus hybrid retrieval + re-ranking and guardrails for reliability. Strong at evaluation/observability (trace logging, LLM-judge, HITL) and at communicating results to non-technical stakeholders via Power BI embeds and Streamlit prototypes.”

Kunal Singh Pundir

Screened

Mid-level Full-Stack Developer specializing in cloud microservices and GenAI systems

USA, USA5y exp

“Built and owned an end-to-end AI-driven decisioning platform at Uber, combining LLM orchestration with typed tool contracts and a Snowflake-based RAG pipeline to make decisions fully auditable. Delivered large-scale measurable impact (120k requests/day, 18k cases auto-resolved/month) while improving ops SLA from 3 days to 6 hours and cutting incident response time nearly in half. Previously led a high-risk strangler-fig modernization of a legacy insurance platform across 120+ microsites at Accenture, coordinating across multiple squads with feature-flagged parallel cutovers.”

Michelle Lu

Screened

Senior Customer Success Manager specializing in B2B SaaS retention and expansion

Pleasanton, CA8y exp

“Enterprise CSM with martech/market-intelligence background (Pulse and Gartner context) who owns accounts end-to-end from onboarding through renewal and expansion. Known for executive-level value narratives (e.g., CPO using benchmarks in a board deck), multi-threading across Product and Legal, and using usage/segmentation analytics plus activation tactics (A/B testing, targeted messaging) to drive adoption and renewals.”

Vagmin Yadav

Screened

Junior Software Engineer specializing in backend systems, ML pipelines, and DevOps

Pune, India2y exp

“TypeScript backend engineer in the robotics domain with hands-on experience building low-latency (20–40ms) production systems using RabbitMQ, Redis, and HA PostgreSQL (Patroni). Has owned end-to-end services supporting 15 clients via config-driven architecture, with strong CI/CD, automated testing, and observability (OpenTelemetry) practices, plus API versioning/deprecation using Keycloak auth.”

Jason Salas

Screened

Senior QA Engineer specializing in game quality ownership, automation, and analytics

Los Angeles, California9y exp

“QA/engineering background spanning Riot Games (VALORANT leaderboard systems) and early-stage startups. Has hands-on experience improving performance and reliability via caching, rate limiting, deduplication/idempotency, and shipping/validating high-stakes production hotfixes; also builds Next.js/TypeScript projects and automation/internal tools (Python).”

Harshana Ragipindi

Screened

Mid-level Support/Software Engineer specializing in incident response, automation, and AWS monitoring

USA4y exp

“Built and owned end-to-end travel booking and baggage fee calculation platforms used by both customer support and customers, emphasizing fast iteration with automated guardrails and production visibility. Experienced designing TypeScript/React systems and operating RabbitMQ-based microservices at scale, including disciplined event contracts, idempotent consumers, and schema evolution strategies. Also created an internal real-time troubleshooting/pricing console that replaced fragmented tools and improved support resolution workflows through pilot-led adoption.”

Arun Gampala

Screened

Mid-level Full-Stack Developer specializing in MERN and AWS microservices

TX, USA4y exp

“Backend engineer with experience at MetLife and Amazon focused on security and control for internal and customer-facing services. Emphasizes contract-first Python/FastAPI APIs with strong auth (JWT + RBAC/claims), data-layer isolation (RLS/tenant scoping), and reliability practices like incremental refactors, rollback planning, and idempotency to handle retry-driven failure modes.”

Lamar Petty

Screened

Mid-level Full-Stack Product Engineer specializing in data-driven web apps and healthcare systems

San Francisco, CA13y exp

“Full-stack engineer with production experience shipping a healthcare-focused web app (Pregnancy-Pal) using Next.js/TypeScript on GCP, integrating a Python/Flask middleware and FHIR server for patient/practitioner dashboards and messaging. Former Wikimedia Foundation Android engineer who led the end-to-end 'Year in Review' feature and built robust automated testing/CI practices (Espresso, GitHub Actions matrix). Strong emphasis on reliability via rigorous validation, comprehensive Postman testing, and detailed API documentation.”

Vedant Kharwal

Screened

Intern AI/ML Engineer specializing in Generative AI and applied machine learning

Mumbai, India1y exp

“New graduate with hands-on LLM work building a RAG pipeline (HNSW, lexical reranking/boosting, ReAct) and optimizing it through ablation to dramatically reduce latency. Also building a modular personal assistant with a custom wake word model, router-driven agent selection, and integrations like Spotify with secrets managed via .env.”

Anandapadmanabhan Santhosh

Screened

Junior Software Engineer specializing in distributed systems and backend microservices

Bangalore, India1y exp

“Distributed systems engineer (ex-Nykaa, Licious) who built a PBFT-based Byzantine fault-tolerant consensus system in Go for a multi-node banking-style application, including checkpointing and automated failover/leader election. Strong production reliability background with Docker, Jenkins CI/CD, and monitoring/on-call troubleshooting using Grafana and New Relic; no direct ROS/robotics hardware experience yet but has highly transferable multi-node coordination expertise.”