Vetted Data Pipelines Professionals

“Significant contributor/maintainer to an open-source JavaScript event-tracking client SDK, owning API consistency/backward compatibility, high-load batching and retry/backoff improvements, and test/CI + documentation upgrades. Diagnosed production-like issues (missing events under load) via reproduction and logging, then reduced GC pressure and improved predictability with a ring-buffer-based batching redesign while actively triaging issues and reviewing PRs.”

“GenAI/LLM engineer who recently built a production compliance assistant at State Farm for KYC/AML and regulatory teams, using AWS Bedrock + LangChain with Textract/Lambda pipelines to extract fields, tag risk, and summarize long documents. Implemented RAG, strict structured outputs, and human-in-the-loop guardrails, and reports automating ~80% of documentation work while reducing review time by ~40%.”

“ML/NLP practitioner with banking experience (M&T Bank) who has built a GPT-4 RAG system using LangChain and Pinecone to connect unstructured customer data with internal knowledge bases, improving accuracy and reducing manual lookup time by 50%+. Strong in entity resolution and productionizing scalable Python data workflows, including major performance wins by migrating bottleneck joins from Pandas to Dask.”

“Backend/full-stack engineer with finance domain experience (State Street) who built and shipped a Kafka-based real-time trade validation system handling 50k+ trades/sec and cut latency by 42%. Also delivered real-time React dashboards (Redux Toolkit/React Query/WebSockets) and operates AWS EKS microservices with GitOps/ArgoCD; has built a FastAPI + LangChain/GPT-4 intelligent document processing service with JWT/RBAC.”

“Led the creation of a software department at a hardware startup and designed/built a platform to manage fleets of hexacopter drones, including tackling the challenge of streaming high volumes of data from many IoT edge devices. Prefers greenfield work with high autonomy, combining hands-on architecture with structured planning, cost estimation, and risk-driven execution.”

“Full-stack product engineer who has shipped polished customer-facing experiences across iOS (SwiftUI), web (Next.js/React/TypeScript), and Python backends. Built systems ranging from an escalating smart-reminder engine to a sub-200ms search UI over 6M+ court records, and owned AWS production operations including resolving a real DB-connection-exhaustion incident with scaling and architectural hardening.”

“Full-stack engineer with healthcare and finance experience who has owned end-to-end production systems across Azure and AWS. Built a real-time clinical dashboard at Centene (React + FastAPI + Azure Event Hubs) that cut data latency from ~12 minutes to under 1 minute and was associated with a 30% reduction in intervention delays. Also delivered MVPs in high-ambiguity environments at Accenture during monolith-to-microservices migration, improving uptime and maintainability with measurable results.”

“Founding/solo engineer who rebuilt an early-stage product from the ground up: Ask NETA, an AI assistant for electricians to answer complex electrical code questions. Delivered a full-stack TypeScript system (React web + React Native iOS/Android, Express API, Postgres on AWS) with CI/CD, observability, and a Vertex AI RAG pipeline, reaching 3,000 MAUs in the first month; also built a real-time distributed scoring system handling unreliable hardware data with sequencing and retries.”

“Data engineer with Charter Communications experience modernizing large-scale AWS data lake pipelines: ingesting S3 data, validating against legacy systems, transforming with PySpark/Spark SQL, and serving via Iceberg/Delta tables. Worked at 50M–300M record scale, delivered >99.5% data match, and built monitoring/alerting (CloudWatch/SNS) plus retry orchestration (Step Functions) and data quality gates (Great Expectations).”

Ramcharan SreenivasaReddy

Screened

Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices

Texas, USA6y exp

“Backend/platform-focused Python engineer who has owned FastAPI services with Postgres/SQLAlchemy and production-grade auth (JWT + RBAC). Experienced deploying and operating microservices on Kubernetes with GitOps (ArgoCD), HPA tuning, and Prometheus/Grafana monitoring, plus hands-on cloud-to-on-prem migrations and Kafka-based real-time streaming pipelines.”

Arunkumar Gangula

Screened

Senior Full-Stack Software Engineer specializing in distributed systems and cloud microservices

Tempe, Arizona11y exp

“Product-minded full-stack engineer from CouponDunia who owned end-to-end notification and recommendation services at million-user scale. Built internal admin/analytics and operations dashboards in React/TypeScript with typed contracts and scalable Node.js REST APIs, and has deep microservices experience with Kafka/RabbitMQ (idempotency, retries/DLQs, partitioning, consumer tuning, and observability).”

Ketan Verma

Screened

Junior Applied AI Engineer specializing in data pipelines and ML systems

College Station, TX2y exp

“Built an end-to-end wafer-data anomaly detection and reporting system at Samsung using PySpark, Random Forest models, SQL, and Grafana to help engineers track faults and take corrective action. Also has strong UX prototyping and validation practices in Figma plus hands-on front-end/full-stack experience (HTML/CSS/TypeScript), including a student project recognized as best design out of 25 teams, and early-stage startup experience pivoting a product based on user interviews into a real-time in-context feedback overlay.”

Rajesh Sivakumar

Screened

Senior Software Engineering Manager specializing in cloud-native distributed systems (FinTech & Healthcare)

San Francisco, CA26y exp

“Engineering leader/player-coach who has led 40+ developers across multiple teams on large financial services web applications (Wells Fargo) and previously delivered a banking mobile app MVP in 6 months with a junior team by setting patterns and CI/CD foundations. Strong in production reliability practices (Splunk monitoring, feature flags, throttled rollouts) and has driven measurable quality/velocity wins, including a 60% faster E2E test framework and a rapid 2-day hotfix during a React 16→18 migration.”

Ashrita Mishra

Screened

Mid-level Data Analyst specializing in analytics, ETL, and cloud data platforms

Jersey City, NJ4y exp

“Data analyst with 4 years of experience spanning banking and retail/marketing analytics. Has hands-on experience building churn analytics pipelines in SQL and Python, optimizing large-query performance, and turning stakeholder-aligned metrics into recurring dashboards and business actions.”

“Analytics professional with hands-on experience building SQL/Python pipelines, customer ID mapping logic, and self-serve BI dashboards across marketing/CRM and regulated aviation reporting environments. Particularly strong in turning messy multi-source data into trusted reporting assets, with repeated claims of major efficiency gains, faster decision-making, and high-confidence stakeholder adoption.”

“ML/AI engineer with hands-on experience building production MLOps systems for predictive maintenance and demand forecasting, including deployment, monitoring, and iterative retraining. Also shipped a RAG-based employee onboarding chatbot integrated with ServiceNow APIs and reports business impact of roughly $300k/month in reduced stockout and overstock costs.”

“Built a production-grade LLM document processing and workflow orchestration platform at CBRE for internal operations teams, handling highly variable long-form documents with a reusable architecture involving 50+ coordinated LLM calls per request. Stands out for treating agentic systems like distributed backend infrastructure, with strong emphasis on evaluation, observability, reliability, and vendor-agnostic orchestration across Bedrock, Vertex AI, and OpenAI.”

Lokesh Jain

Screened

Senior AI/ML Engineer specializing in supply chain and healthcare systems

Bentonville, AR6y exp

“Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.”

“Graduate student who has built both full-stack web products and an offline Android AI assistant for visually impaired users. Particularly interesting for roles spanning product engineering and applied AI, with hands-on experience in on-device ML, privacy-sensitive deployment, and making complex AI interactions usable for non-technical users.”

“Built and significantly owned enterprise project-finance dashboards at Publicis Sapient, with a strong focus on performance, data freshness, and trust for demanding finance users. Stands out for diagnosing problems across both the browser and data layers—optimizing SQL, reducing DOM load, and redesigning interactions so users stopped exporting to spreadsheets and worked directly in the live dashboard.”

“Full-stack engineer with recent startup-style experience at SynapOne building enterprise B2B SaaS platforms for compliance and operational review workflows. Stands out for turning ambiguous business problems into production systems, including AI-assisted workflow automation, scalable Go/Python microservices, React/TypeScript interfaces, and PostgreSQL/Elasticsearch-backed platforms used daily by customers.”

Muhammad Ali

Screened

Senior Full-Stack Engineer specializing in cloud-native FinTech and AI systems

Virginia, USA9y exp

“DevOps-focused engineer with 8 years of hands-on experience in early-stage startup environments, working on small teams to modernize CI/CD and Kubernetes deployments. They report reducing release times from hours to minutes, improving reliability and production recovery, and building backend APIs and automation for an internal SaaS platform shaped by security, scale, and compliance requirements.”

Mac Tichner

Screened

Principal Software Engineer specializing in full-stack platforms and AI integration

Miami, FL14y exp

“Serial entrepreneur and software engineer currently ideating a B2B vertical AI SaaS company with seed funding secured, using a custom-built AI agent to generate and vet startup ideas. Previously sold a software product (AskDiagnostic) into physician offices and spun an observed workflow gap into an in-house compounding solution, including a <3-minute dispensing process and supporting software for inventory, compliance, labeling, reorders, billing, and reporting.”