Vetted PostgreSQL Professionals

Sumanth Gottipati

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY4y exp

“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”

EMMANUEL ETIENNE

Screened

Engineering Manager specializing in FinTech money movement and AI-driven infrastructure

Brooklyn, NY12y exp

“Player-coach fintech engineer/engineering lead who built a deterministic payer-ID wire reconciliation system with Citi, including idempotent ingestion and webhook processing across Ruby and Go, materially reducing accounting manual work. Experienced in incident response (Plaid-related customer-impacting issue), stakeholder-driven MVP scoping for ACH status visibility, and delivery acceleration via infrastructure templating (EC2) and standardized Magento project setups.”

Soham Ravindra Lokhande

Screened

Junior Software Engineer specializing in agentic automation and AI platforms

Washington, DC2y exp

“Backend-leaning founding/early engineer who built automation platforms end-to-end: FastAPI/Python services integrated with a Next.js/TypeScript frontend, including a production VNC streaming URL endpoint for cloud-instance desktop viewing. Also designed core Postgres user/workflow data models and built an agentic orchestration system with LangChain/LangGraph (sub-agents, validators, pause/resume), plus made scalability tradeoffs like S3 pre-signed uploads to keep microservices responsive.”

Alankrit Srivastava

Screened

Intern Data Engineer specializing in Snowflake pipelines and AI/ML analytics

Houston, TX3y exp

“Built and operated an end-to-end TypeScript/Node AI agent platform for high-volume financial data that generates explainable investment signals and automates execution via resilient Playwright browser automation. Uses Postgres + pgvector/Prisma for RAG retrieval, Redis for async orchestration, Zod-based boundary validation as a circuit breaker, and OpenTelemetry for tracing/latency monitoring; also designed a TypeScript SDK with semver, scoped bearer-token auth, CLI key rotation, and interactive Swagger docs.”

“Commercially minded candidate with exposure to private equity firms as sales targets and experience building partnerships around venture-backed company ecosystems. They appear more inclined to join an existing company than found one, bringing a metrics-driven, process-oriented approach and creative execution style with a strong focus on clear growth paths and capital stability.”

“Analytics professional with hands-on experience building SQL and Python workflows across SAP, Oracle, and internal operational systems, processing roughly 5 million records per month. They combine strong data quality rigor with stakeholder-friendly Power BI reporting, and cite a concrete impact of cutting reporting turnaround time from four days to two while surfacing cost anomalies for business teams.”

Hari Billa

Screened

Mid-level Data Scientist specializing in machine learning, NLP, and healthcare AI

USA3y exp

“Senior data scientist with hands-on ownership of production ML and GenAI systems across enterprise churn, clinical Q&A, and real-time fraud detection. Stands out for combining strong MLOps discipline with measurable business impact, including $2M+ retained revenue, 10K TPS low-latency fraud infrastructure, and a clinician-reviewed RAG system that improved retrieval accuracy by ~38%.”

SREYAS GANGJI

Screened

Mid-level Software Engineer specializing in AI/ML backend systems

Chicago, IL4y exp

“AI/data engineer at ZS Associates focused on production-grade agentic systems, FastAPI microservices, and cloud-native ETL/RAG pipelines at significant scale. They’ve built multi-agent validation and diagnostic workflows inspired by their Copilot/KUBEPILOT AI work, supporting 500K+ records per day while improving ML inference performance by ~30% and cutting manual troubleshooting by 60%.”

Dishank Kailash Oza

Screened

Mid-level Software Engineer specializing in distributed systems and cloud infrastructure

Santa Clara, CA4y exp

“Engineer with a thoughtful, production-oriented approach to AI-assisted development, including multi-agent workflows for planning, coding, review, testing, and debugging. Stands out for treating AI systems like distributed pipelines with explicit interfaces, validation layers, and guardrails to improve reliability and reduce hallucinations.”

Ramya Sree Kanijam

Screened

Mid-level Software Engineer specializing in backend systems, cloud, and AI pipelines

Remote, USA3y exp

“Built and owned an end-to-end AI-driven content enrichment pipeline for a news workflow, using n8n, LLM agents, and external APIs to automate ingestion, deduplication, categorization, and approval routing. Stands out for production-minded AI systems work: they improved reliability with schema validation, retries, idempotency, and monitoring, while automating 90% of processing and cutting duplication errors by 95%+.”

Raj Kale

Screened

Junior Software Engineer specializing in full-stack systems and FinTech

Los Angeles, CA3y exp

“Full-stack engineer with experience building financial and hiring-product systems, spanning React/TypeScript dashboards, Flask/Kafka/Postgres backends, and multi-tenant configuration for 3,000+ clients. Stands out for combining deep technical debugging and performance work with product-minded UX improvements, including a 41% lift in resume matching accuracy and ~40% latency reduction through batching and query tuning.”

Dinesh Guguloth

Screened

Mid-level Software Engineer specializing in full-stack cloud-native and AI applications

New York, NY4y exp

“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”

Nidhip Patel

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack development

United States3y exp

“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”

Sairam Prasad

Screened

Mid-level Full-Stack Engineer specializing in AI-powered web platforms

United States4y exp

“Fullstack engineer focused on AI-powered customer-facing products, with hands-on experience building semantic search, document intelligence, and story-analysis platforms from scratch. Stands out for owning architecture and implementation across React/Next.js frontends, GraphQL/FastAPI backends, and async AI pipelines, while also shaping product direction through direct customer feedback in ambiguous startup environments.”

“Sole full-stack engineer on a founding team building an AI-native construction management SaaS, where they owned the document search interface, project explorer, and ingestion pipeline end-to-end. They also shipped a multimodal conversational AI experience for social-skills practice, showing a blend of product sense, AI integration, and startup-speed execution.”

Julia Vavrinyuk

Screened

Senior Software Engineer specializing in cloud, GenAI, and SaaS solutions

Remote, USA9y exp

“Candidate combines B2B SaaS sales experience with hands-on technical delivery, spanning full-cycle selling at Consensus Cloud Solutions and GenAI POC leadership at Capgemini. Particularly interesting for Solutions Engineering roles that need someone comfortable with enterprise demos, AWS-based AI architectures, regulated-industry customers, and translating technical trade-offs into business decisions.”

“Full-stack Java developer from Cognizant who built a real-time transaction monitoring and tracking platform for operations and customer visibility. Stands out for combining Spring Boot, React/TypeScript, Kafka, and CI/CD tooling to ship near real-time dashboards, while also working directly with users to refine requirements and improve performance in high-volume transaction environments.”

“Hands-on AI/LLM practitioner who built a RAG-based customer support chatbot and tackled production issues like data chunking complexity and response-time lag. Uses techniques such as overlapping chunks, semantic search, context engineering, and query routing, and has experience presenting technical demos/workshops to developer audiences.”

“Backend/data engineer who built a production booking platform on FastAPI microservices (Postgres/Redis/gRPC) and delivered AWS infrastructure spanning Lambda, ECS, SQS, and Glue-to-Redshift analytics. Demonstrated measurable SQL optimization (10 minutes to <40 seconds) and strong operational ownership through monitoring, incident response, and schema-evolution hardening.”

“AI Backend Engineer in MetLife’s claims technology group who built and deployed a production LLM-based decision support system that helps claim adjusters quickly find relevant policy rules from long PDFs and historical notes. Designed it as multiple production-grade services with retrieval-first guardrails, continuous validation, and Airflow-orchestrated pipelines for ingestion, embeddings, and vector index updates to keep the system reliable as policies and data evolve.”

“Built and deployed an LLM/applied-ML system enabling efficient extraction of useful information from large unstructured multimodal datasets, owning the full pipeline from ingestion to inference and APIs with a strong emphasis on production reliability, latency, and monitoring. Also delivered a voice-based AI workflow for Hindi policy document access for the Election Commission of India by translating non-technical usability needs into iterative demos and a successful implementation.”

“Backend/platform engineer with production experience building a Python SDK over a microservices ecosystem, emphasizing reliability (JWT auth, retries/timeouts, custom exceptions) and integration testing. Has delivered AWS EKS microservices with Jenkins+Helm CI/CD, strong secrets/config separation using AWS Secrets Manager, and set up Datadog APM/deployment/change monitoring. Also modernized legacy VB applications to C#/.NET WPF via incremental migration with parity testing and stakeholder sign-off.”

“Built a production RAG-based healthcare chatbot to retrieve patient medical documents spread across multiple platforms, reducing manual and error-prone searching. Implemented semantic search with custom embeddings (Hugging Face) and Pinecone, deployed via FastAPI/Docker on AWS SageMaker with MLflow tracking, and optimized fine-tuning cost using LoRA while orchestrating retraining pipelines in Airflow.”

“GenAI/LLM engineer who built and deployed a production RAG system for enterprise document search and decision support, cutting manual lookup time by 40%+. Experienced with LangChain/LangGraph agent orchestration plus Airflow/Prefect for ingestion and incremental reindexing, with a strong focus on reliability (testing, observability) and stakeholder-driven metrics.”