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Vetted PostgreSQL Professionals
Pre-screened and vetted.
Nishitha Thummala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference
“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”
Sahil Sinha
Mid-Level Software Engineer specializing in full-stack development, cloud, and data infrastructure
“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”
Aravind Sudha
Director-level engineering leader specializing in cloud platforms and distributed systems
“Senior engineering leader at AWS currently managing two services in the MSK organization, including Replicator for disaster recovery/data distribution and Glue Schema Registry. He combines hands-on distributed systems depth with large-scale people leadership, having managed teams up to 32 engineers and coordinated platform onboarding work across roughly 340 AWS services. Earlier experience in payroll and compliance platforms adds strong enterprise domain breadth beyond cloud infrastructure.”
Dilpreet Singh
Executive CTO and Founder specializing in AI platforms and hyper-scale SaaS
“CTO-minded builder seeking to join a startup; previously created an AI-driven platform that abstracted away DevOps and infrastructure for drug discovery researchers. Emphasizes high-leverage, zero-to-one execution with managed cloud/open-source tooling, and a strong reliability/reproducibility mindset validated against existing scientific pipelines.”
Nikhil Reddy
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”
Krishna Reddy
Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants
“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”
Alfred Dwan
Intern Software Engineer specializing in AI, cloud-native systems, and MLOps
“Backend/full-stack engineer who has owned a production recruiting platform end-to-end (TypeScript/Node microservices for scraping/cleaning/serving job data, RabbitMQ for spike handling, MongoDB + Elasticsearch, AWS containers) with pragmatic CI, logging/alerts, and Docker Compose E2E tests. Also operated high-traffic event pipelines during a Binance internship using Kafka + Redis idempotency, with strong observability and failure-mode/rollback/degradation practices, and has experience designing developer-friendly REST APIs and resilient browser automation for E2E flows.”
UDAY JARAJAPU
Executive engineering leader specializing in AI-native products and large-scale platforms
“Experienced cross-functional operator with background in AI, edtech, consumer mobile, cloud, and real estate search, including roles at Apple, AWS, and Trulia. Currently building Typerighter, an AI-native writing workspace focused on compliance, authenticity, and human-verifiable content, with a nuanced understanding of institutional requirements and startup/accelerator dynamics.”
Graham Lutz
Director of Engineering specializing in platform, AI, and cloud-native SaaS
Dinesh Mishra
Executive AI Product Leader specializing in FinTech and agentic AI platforms
“Fintech/neobank CTO (5+ years across US and UK markets) now building Payzo Money, a fintech copilot for SMBs covering expenses, accounting, invoicing, and payroll. Pre-revenue and seeking a $5M seed round, with active Bay Area conversations and a clear focus on bank sponsorship plus compliance/operations readiness; leverages Claude-based AI agents to accelerate building with limited resources.”
Shuvam Mitra
Mid-level Data Scientist specializing in anomaly detection and production ML
“Interned at Backblaze building production AI systems for incident response and security operations, including an internal LLM-powered incident triage assistant that used Snowflake + RAG over historical tickets/postmortems and delivered results via Slack and a web UI. Emphasizes reliability (PII filtering, grounding, schema validation, fallbacks) and rigorous evaluation/observability (offline replay, partial rollouts, time-to-first-action metrics, Prometheus/Grafana).”
Dexin Huang
Junior AI Engineer specializing in LLM systems, RAG, and full-stack automation
“Built and deployed an AI receptionist product for field-service businesses (HVAC/electrician), including real-time Jobber scheduling integrations and Twilio-based calling. Combines hands-on customer/operator shadowing with strong production engineering (queueing to handle API limits, rigorous testing/mocking, mirrored prod environment) and cross-layer troubleshooting, driving user adoption through review/override workflows.”
Shilong Li
Intern Software Engineer specializing in backend and distributed systems
“Backend engineer with experience at ByteDance (TikTok monetization) and Baidu, plus a personal real-time course booking/tracking platform built with FastAPI, Postgres, and Redis. Demonstrates strong concurrency and reliability engineering (Redis distributed locks with TTL extension, idempotent event processing) and practical DevOps skills (Kubernetes/Helm, GitLab CI/CD, Docker build-time optimization).”
Amrita Pritam
Senior Backend Engineer specializing in distributed microservices and event-driven systems
“Backend engineer with production experience building a high-scale notification pipeline (~20M/day) using Java/Dropwizard with Kafka and Azure Queue, including DLQ/poison-message handling and the outbox pattern for reliability. Also led a batch-based migration of Yammer Messaging user data from PostgreSQL to Azure Cosmos DB for global multi-region scale, addressing throttling and network failures via retries, escalation policies, and dynamic throughput tuning.”
Pranav Hariharane
Mid-Level Backend Engineer specializing in REST APIs and AWS
“Backend engineer who built a new REST eligibility service at Barclays that unified siloed account logic (card/loan/deposit) and integrated with web/mobile, ultimately serving millions of users daily. Also built an end-to-end LLM-based pharmaceutical care-plan generation tool in a rapid Columbia startup competition, emphasizing configurable design, strict validation, persistence, and robust error handling.”
Gabrielle Burns
Senior AI/ML Engineer specializing in computer vision, NLP, and enterprise ML systems
“ML/AI engineer with hands-on ownership of production computer vision and GenAI systems, spanning real-time public safety video analytics and RAG-based knowledge assistants. Stands out for translating research-oriented approaches into scalable, monitored production systems with clear business impact, including 50% latency reductions, 25% faster response times, and 40% lower document search time.”
MARCUS JOHNSON
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
Sai Gundeti
Mid-Level Backend Software Engineer specializing in distributed systems and billing platforms
“Full-stack engineer with Uber experience building finance/billing reconciliation systems: shipped and owned an internal operations dashboard (Next.js App Router/TypeScript) that cut investigation time from hours to minutes and improved load time from ~6–7s to <2s. Deep in Postgres modeling and performance (sub-200ms optimized queries) plus durable event-driven workflow orchestration with idempotency, retries/backoff, DLQs, and reconciliation jobs; also has seed-to-Series C startup experience emphasizing end-to-end ownership.”
Anna Huang
Mid-level Software Engineer specializing in backend distributed systems and cloud platforms
“Software engineer at Intel who owns a production Go/Kubernetes backend for supply-chain transparency and end-to-end hardware integrity verification in a hybrid cloud setup (AWS control plane + Azure data plane). Also built and shipped an AI agent workflow for real-estate due diligence that turns raw Excel spreadsheets into structured investment outputs and auto-generated PowerPoint insights using LangGraph, with strong emphasis on verification, observability, and reliability guardrails.”
Aniket Singhal
Senior Software Engineer specializing in AWS-based distributed systems and FinTech platforms
“Backend engineer with Amazon experience building large-scale, automated financial/accounting and pricing systems on AWS. Designed a fault-tolerant Step Functions + DynamoDB workflow platform handling 100K+ messages/sec to compute fair values and generate journal entries in under 3 seconds, and led safe API refactors using shadow mismatch testing. Also uncovered a major legacy pricing bug (tax vs non-tax swap) that cut mismatch rates from 5–10% to ~0.5% and materially improved price acceptance/business outcomes.”
Michael Kaufman
Mid-Level Full-Stack Software Engineer specializing in mobile and web platforms
“iOS-focused engineer who led feature development for Amazon Books/Kindle (e.g., Series & Story So Far recaps, Kindle Memories) and introduced pure Swift packages while building sync and content download systems. Also has full-stack experience (React/TypeScript + Node with REST/GraphQL) and strong AWS operations (CDK/CI-CD, CloudWatch, canaries, autoscaling), plus founder experience at GLXY.ai shipping an early hardware MVP (weight sensors) under tight constraints.”
kartik kanotra
Mid-level Software Developer specializing in cloud data engineering and MLOps
“Software engineer with strong AWS production experience, including an end-to-end historical backfill system exporting ~10PB of CloudWatch logs into a data lake using Step Functions/Kinesis/Lambda/Firehose/Glue. Emphasizes reliability and operability (DynamoDB checkpointing, monitoring dashboards, CI/CD with canary tests) and has also built customer-facing UI work for the Visa Developer Portal using Angular + Spring Boot, plus React/Redux frontend work.”
Danny Niedzwiedzki
Mid-level Frontend Software Engineer specializing in accessible React and Next.js applications
“Frontend engineer with 8+ years of React experience who owned a sophisticated enterprise chatbot embedded in third-party client sites at massive scale. Stands out for combining deep browser/iframe architecture knowledge, accessibility leadership, performance optimization, and security-driven Next.js migration work in a multi-tenant product used by large enterprises.”
Jim Glassman
Executive Technology Leader specializing in Enterprise AI, Cloud Architecture, and Data Platforms
“Senior data/technology executive who stays hands-on: currently building a Go micro-kernel orchestration layer for medical AI agents to boost concurrency and enforce HIPAA/PHI controls, achieving 26x throughput on migrated workloads. Has led large-scale transformations across healthcare and financial services, including a 45-day data warehouse rebuild at Elara Caring and a data/ML roadmap at Acelity credited with $230M in annual revenue impact prior to 3M acquisition.”