Vetted Data Pipelines Professionals

Gautam Agrawal

Screened

Mid-Level Software Engineer specializing in backend systems, cloud, and applied LLM/NLP

IN, USA4y exp

“Applied LLMs to classify long nonprofit mission statements into 8 segments without labeled data, using an ensemble of clustering/embedding methods plus zero-shot RoBERTa/BART and a Tree-of-Thought prompting pipeline with LLM-as-judge evaluation (Gemma). Also built LangChain/LlamaIndex agentic RAG workflows including a text-to-SQL data analysis assistant grounded on DB schema with retries and performance optimizations on an HPC cluster.”

Karan Savaliya

Screened

Junior Backend Engineer specializing in data platforms and cloud APIs

Remote, USA1y exp

“Backend lead at a stealth startup and builder of MailIQ/MailBox—an automated Gmail inbox digest + cleanup system. Designed secure multi-account email ingestion and cost-efficient LLM-based summarization, and implemented robust unsubscribe automation using Playwright + OpenAI webpage analysis (including captcha-handling) with strong safety guardrails, incremental rollouts, and rollback strategies.”

“Backend/AI engineer who built Matchable, an end-to-end AI-powered workforce matching platform using FastAPI, transformer-based NLP, PostgreSQL, and AWS, with a strong focus on practical system design tradeoffs. Also brings research-oriented experience from Los Alamos/ASU simulation work and has built multi-agent LLM workflows with schema validation and auditability, suggesting a thoughtful approach to reliability in AI systems.”

“Built and shipped a production AI/LLM agent-based, event-driven credit underwriting/decisioning workflow that automated document understanding, retrieval, risk scoring, and compliance checks—cutting turnaround from ~90 days to ~5 minutes while boosting throughput 200x+ and approvals ~50%. Experienced with Airflow/Prefect orchestration, Redis/RabbitMQ queues, rigorous eval/monitoring, and close collaboration with non-technical underwriting teams.”

“Full-stack engineer with fintech payments experience who shipped an end-to-end guest invoice payment flow emphasizing reliability under retries/failures (idempotency via DynamoDB, async processing with Lambda/EventBridge/SQS + DLQ). Also built a FastAPI backend with Cognito/JWT + scoped guest tokens and a polished React/TypeScript checkout UX, and has performance-focused Postgres/Redis design experience for flash-sale e-commerce workloads.”

Homak Patel

Screened

Junior Software Engineer specializing in Agentic AI and Data Systems

2y exp

“Forward Deployed Engineer at EasyBee AI who productionized a self-storage customer’s multi-agent LLM system end-to-end—rebuilding it with LangGraph/CrewAI, integrating with real property management + CRM systems via an MCP server, and adding observability/guardrails for reliable daily use. Experienced in live troubleshooting of agentic workflows, developer demos/workshops (including an open-source project, MerryQuery), and partnering with sales to close deals through customer-specific technical demos and fast integration feedback loops.”

Annie Suzan Edwin Arokiaraj Caroline

Screened

Junior Full-Stack Software Engineer specializing in distributed systems and data pipelines

Tempe, AZ1y exp

“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”

Himanshu Shivkumar Garg

Screened

Senior Full-Stack Java Developer specializing in Healthcare IT and FinTech

Florida, USA4y exp

“Built and owned an end-to-end HIPAA-compliant Next.js/TypeScript portal at Casedok using a microservices, event-driven architecture with Temporal-orchestrated SAGA workflows. Emphasizes production-grade quality (strict typing, Jest integration tests, CI + mandatory PR reviews) and operational reliability/observability (circuit breakers, idempotency, Prometheus alerts), plus experience designing external-facing APIs with Swagger, JWT, and backward-compatible versioning.”

“Data analytics and BI professional with experience turning messy institutional and customer data into decision-ready reporting and predictive systems. They combine strong SQL/Python execution with end-to-end ownership of churn analytics, stakeholder alignment, and operational rollout into dashboards and CRM workflows.”

“Built and owned a production-grade RAG/LLM support automation system on AWS using GPT-4, Pinecone, FastAPI, and Redis, taking it from initial experimentation through deployment, monitoring, and iterative improvement. Their work reduced support workload and ticket volume by about 40%, improved CSAT and self-service resolution, and they also created shared Python/LLM infrastructure that accelerated other teams' delivery from weeks to days.”

“Built and shipped an end-to-end AI-powered portfolio chatbot, owning the React frontend, FastAPI backend, and FAISS-based retrieval layer. Demonstrates hands-on full-stack product thinking with attention to UI performance, TypeScript maintainability, and post-launch iteration on response relevance and speed.”

“Software/product engineer who owns customer-facing internal platforms end-to-end, with deep experience building data pipeline health and data quality tooling (near-real-time alerting and ops dashboards). Strong in React/TypeScript + Python REST architectures and microservices with RabbitMQ, emphasizing reliability patterns (idempotency, DLQs, correlation IDs) and fast, safe iteration via feature flags, testing, and observability.”

“Built and deployed a production generative-AI copilot at Tungsten that automates invoice/form extraction template creation, reducing weeks of manual model-building work. Combines fine-tuned LLMs (PyTorch/HuggingFace) with OpenCV layout grounding to reduce hallucinations, and runs an end-to-end Kubeflow-based MLOps pipeline with drift monitoring, canary releases, and automated retraining.”

“Product-minded engineer who has owned features end-to-end, including a full onboarding redesign that lifted completion ~25% and a production LLM/RAG report-generation system with strong guardrails (schema-constrained JSON, confidence gating, logging) and an automated eval/regression loop built from real user queries. Also built a scalable research data pipeline ingesting messy PDFs/JSON/CSVs with normalization, idempotent reruns, observability, and cost/latency tradeoffs.”

“Backend/data engineer who has owned end-to-end production pipelines and data services, processing ~500K–1M records/day from APIs/logs into MySQL and serving via REST APIs. Strong focus on reliability and data quality (ELK + structured logging/monitoring), with measurable improvements (~30% reduction in bad data, ~20% query performance gains) and experience operating external data collection/scraping systems with anti-bot and schema-change resilience.”

Rethvick Sriram Yugendra Babu

Screened

Junior AI/ML Software Engineer specializing in Generative AI and scalable data pipelines

Tucson, AZ2y exp

“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”

Mayank VYAS

Screened

Mid-level AI/ML Engineer specializing in LLM agents, RAG retrieval, and IoT ML systems

Tempe, AZ4y exp

“Built production LLM-driven products including a job-hunt AI (job ranking + resume optimization) and an InterviewAI agentic pipeline using LangChain. Focused on practical deployment concerns like securing OpenAI usage via rate limiting and tiered quotas, and demonstrates an applied approach to choosing models, retrieval methods (RAG), and prompting strategies.”

MUNI CHARAN SINGAMALA

Screened

Mid-level Data Analyst/Data Engineer specializing in SQL, ETL pipelines, and BI dashboards

Florida, USA4y exp

“Built and supported a production analytics backend (Python, PostgreSQL/Teradata, Airflow) powering KPI/reporting dashboards, and resolved peak-time latency/timeouts through systematic SQL tuning (EXPLAIN ANALYZE, indexing, query rewrites, pre-aggregations). Also shipped an applied AI-style feature that generates plain-language report summaries from pre-computed metrics with validation, monitoring, and fallback to manual review.”

“Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.”

“Unity lead developer who built a turn-based soccer game (Soccer Glory/Score Hero-like) with complex in-air ball simulation, AI reactions, and animation handling, then scaled production by creating an in-editor level/animation authoring tool that saves to JSON and shifted level setup from devs to designers. Strong multiplayer background across Photon PUN, Mirror, UNet, and Socket.IO, including a 100-user metaverse room and practical approaches to authoritative simulation and VR/mobile performance optimization (Meta Quest 90 FPS).”

“Software engineer with hands-on production experience deploying Spring Boot services to AWS using Docker and Jenkins CI/CD, focused on stable releases, easy rollback, and performance improvements through monitoring/logging and query optimization. Has proven cross-layer troubleshooting skills (identified packet loss causing intermittent timeouts via network traces) and experience collaborating on-site with operators in industrial/IoT-style environments, including working alongside robotics/PLC teams.”

“Built and deployed a production AI accessibility platform that turns chart and image-based graphs into real-time audio narratives for visually impaired users. Implemented a ResNet-based CV + OCR + NLP + TTS pipeline and improved performance through preprocessing, Redis caching, and Kubernetes autoscaling/rolling updates on AWS to handle traffic spikes with no downtime.”

CharanKumar Pathakamuri

Screened

Entry-Level GenAI/LLM Engineer specializing in agentic systems and RAG

Baltimore, MD1y exp

“LLM/AI agent engineer with consulting/contract experience (Kanhaiya Consulting LLC) who deployed a production AI agent to automate BIM list workflows end-to-end—from database understanding and data cleaning to automated visualizations/dashboards. Worked around restricted real-time data access by generating synthetic data and improving outputs via supervised fine-tuning, and uses AWS-based LLMOps observability (Opic/OPEC) plus hybrid retrieval (vector+BM25 with reranking) to optimize relevance, latency, and cost.”