Vetted PostgreSQL Professionals

“Built production LLM systems focused on reliability and safety, including a plain-English deployment tool that generates validated plans and provisions to Kubernetes while preventing unsafe actions via schema enforcement and plan/execute separation. Also created multi-LLM workflows (LangGraph) and stakeholder-friendly demos at Bosch, including a PyQt/FastAPI/CUDA app comparing SAM2 vs SAMWISE for on-device object detection with intuitive UX for business users.”

“Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.”

“Backend-leaning engineer with experience at Dropbox, Wayfair, and Etsy who has led cross-product integrations and internal platform tooling. Re-architected a legacy promo code system from a PHP monolith to a Java/Spring Boot microservice achieving a 99% execution-time reduction, and built a React/TypeScript + Supabase product (press.social) with LLM-powered bulk parallel generation and a path to multi-tenancy.”

“Full-stack engineer (Snowflake) who shipped an AI/LLM-powered data exploration product end-to-end, spanning Spring Boot/Python services and a polished React UI with streaming responses and robust fallbacks. Experienced operating high-scale AWS deployments (Docker/Kubernetes, SNS/SQS, RDS Postgres, CloudWatch, Jenkins CI/CD) supporting thousands to tens of thousands of concurrent users, including handling real traffic-spike scaling incidents.”

Raghu Prabhudeva

Screened

Staff Embedded/Automotive Systems Architect specializing in IVI, ADAS, and digital cockpit platforms

USA

“Robotics-adjacent software engineer with hands-on ROS 2 experience building and integrating sensor nodes (IMU, GNSS, wheel encoder) and working with distributed pub/sub concepts via ROS IDL and DDS. Also has Gazebo exposure through Udacity coursework and uses Docker as a core development/deployment tool, with related experience in automotive camera-based solutions.”

greg farhadian

Screened

Senior Software Engineer specializing in cloud data platforms and Java microservices

Remote4y exp

“Backend/data engineer with experience building Kafka-driven real-time pipelines that support ML code deployment and downstream integrations. Currently migrating high-throughput mainframe (COBOL/assembly) processing to Java, using Spark/Databricks to preserve performance and employing rigorous A/B testing across dev/pre-prod/prod with years of historical data.”

Sandeep Rohilla

Screened

Principal Platform Engineer specializing in AI-driven document automation

San Francisco, CA20y exp

“Backend engineer who built an event-driven, multi-service resume review system integrating AI/ML workflows. Demonstrated strong performance engineering (e.g., composite indexing dropping latency from ~600ms to ~35ms and major P95 gains) and high-throughput pipeline optimization via caching, batching, and worker concurrency tuning, with multi-tenant isolation implemented across DB and Redis.”

Yash Jajoo

Screened

Senior Software Engineer specializing in AI and FinTech platforms

New York City, NY8y exp

“Built a production LLM pipeline at Walter AI that scans massive user inboxes, identifies financial newsletters, and extracts trading strategies into structured JSON for downstream paper-trading workflows. Stands out for combining agent architecture with strong production discipline—cutting scan time from 20 to 5 minutes, reducing LLM costs by 90%, and achieving 3-second P99 latency while handling messy, inconsistent email data at scale.”

“Backend engineer with end-to-end ownership of scientific and AI-powered systems, including neuron imaging pipelines at Monell Chemical Senses Center and an LLM-based structured information extraction platform for Wharton and PSG. Stands out for turning messy, compute-heavy workflows into reliable production backends with measurable impact, including saving researchers over 50 hours per week.”

“Built both traditional data infrastructure and LLM-powered product workflows, spanning a Python/SQL ETL deployment at Amazon and an adaptive learning system for their DataLingo platform. Particularly interesting for roles at the intersection of data engineering, applied AI, and customer-facing product delivery, with hands-on experience stabilizing probabilistic LLM systems in production.”

“Software engineer with practical, day-to-day experience embedding AI into development workflows across coding, testing, code review, and AWS data pipelines. Uses tools like Claude, Cline, JUnit, Mockito, and Amazon Bedrock, and stands out for having a realistic, mature view of agent limitations, hallucinations, and the need for strong prompting and human validation.”

Robert Davis

Screened

Staff Software Engineer specializing in backend and distributed systems

Remote, US19y exp

“Backend engineer who co-launched SkyKick’s Office 365 SharePoint/Exchange backup product, built the MVP, and then architected and led its design for 9 years. Stands out for high-scale systems expertise, including an algorithmic redesign that cut cloud costs by an order of magnitude, plus earlier experience integrating speech recognition systems in noisy real-world customer environments.”

“Senior software engineer candidate who uses AI and multi-agent workflows thoughtfully to speed up development while preserving engineering rigor for production-critical decisions. Stands out for a clear risk-based framework: leveraging agents for boilerplate, refactoring, testing, and debugging, while relying on fundamentals, metrics, and human review for system design and scalability.”

Akhilesh Patil

Screened

Junior AI/ML Engineer specializing in FinTech and generative AI

Remote, USA2y exp

“Built an end-to-end AI bug triage dashboard that combined React/TypeScript, FastAPI, Postgres, and classical ML to reduce manual engineering triage work by about 40%. Stands out for pragmatic, product-minded AI engineering: choosing interpretable models when they were sufficient, designing human-in-the-loop UX for trust, and separately building an agentic RAG project with vector search, Neo4j knowledge graphs, and reranking.”

Ethan Hu

Screened

Entry-level Software Engineer specializing in full-stack and embedded systems

Seattle, WA1y exp

“Backend/full-stack engineer on Qualtrics' Online Samples team working on audience sampling systems and APIs used by researchers. They have hands-on ownership of TypeScript/React/Express services, emphasize multi-layer testing and production observability with Splunk/VictorOps, and have built APIs for both internal and external developers.”

“Solutions engineer with recent experience in semiconductor and manufacturing SaaS, spanning pre-sales demos, SOW/POC authoring, on-site deployments, and production integrations. Particularly notable for bridging factory-floor equipment, on-prem Java applications, and Azure cloud systems, while also operating in highly regulated NIST 800-53 defense environments.”

“Software engineer with experience spanning early-stage startup architecture and large-scale Amazon product development. They’ve driven search and data-platform decisions in a 20-person startup, built full-stack React/Python tools that automate internal workflows, and shipped marketplace expansion and personalization features impacting 200k sellers and millions of end users.”

“Full-stack engineer with experience spanning a lean startup at AppLovin and production financial systems at Vanguard. They’ve built core user-facing platforms from scratch, including a B2B advertiser/publisher dashboard and a resilient client onboarding system using Spring Boot, NestJS, Postgres, Kafka, Redis, and AWS. Particularly strong in ambiguous environments where they work directly with stakeholders and own delivery end to end.”

“Built and owned an LLM support copilot at Stripe focused on improving agent ticket resolution. Designed the backend and ML system end to end, using RAG, Redis caching, hybrid vector search, and LoRA fine-tuning to achieve 40% lower latency and 22% higher response accuracy, with continuous quality monitoring via Ragas and related evaluation frameworks.”

Josh Rhoades

Screened

Executive Technology Leader (CTO) specializing in AI-enabled SaaS and regulated platforms

Los Angeles, CA30y exp

“Senior engineering leader with experience at Disney and BlackLine who drives business-aligned technology roadmaps through deep Product/Engineering partnership (two-in-a-box) and pragmatic prioritization frameworks. Has led major modernization initiatives—private-to-public cloud migration to GCP with multi-cloud evolution, data-layer performance improvements (Mongo/Redis, caching/query optimization), and tooling upgrades (VSS to GitHub)—while scaling teams with strong quality and accountability culture.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”