Vetted NoSQL Professionals

“Built internal product features at Sysco's Collab Cafe across React/TypeScript frontend and Spring Boot/PostgreSQL backend, including a full project invite flow and an early AI-style project matching capability. Stands out for owning features end-to-end, improving React dashboard performance with profiling and component refactoring, and making pragmatic 0→1 tradeoffs to ship quickly.”

Katha Naik

Screened

Intern software engineer specializing in AI, cloud, and full-stack systems

Fremont, CA2y exp

“Engineer with experience at Fox Corporation and Qualcomm, focused on production automation and AI-powered systems. At Fox, they built a serverless Bedrock Operations CoPilot for broadcast/media operations that centralized fragmented operational data and cut incident investigation time by 50-60% across distributed teams and stations. They also bring applied LLM experience from Qualcomm, where they worked on a safer RAG-based learning assistant for children with autism spectrum disorder.”

“Master’s CS candidate with backend internship experience modernizing live operational workflows at NatWest/NetWess, focusing on reliability improvements, safer CI/CD deployments, and incremental refactors using feature flags and rollback paths. Built FastAPI-based APIs with strong security patterns (JWT + 2FA/TOTP, centralized authorization, RLS) and demonstrated attention to edge cases like idempotency and data consistency in a Netflix-clone project.”

“Backend-focused engineer at Wells Fargo owning production payments features end-to-end, including Spring Boot REST services, CI/CD + containerized AWS deployments, and CloudWatch-based observability. Has hands-on experience stabilizing high-traffic transaction workflows and building reliable ingestion/integration flows using idempotency, retries/backoff, and reconciliation.”

“Insurtech R&D leader turned CTO with 25+ years across telecom, DoD, automotive, and commercial insurance. Built patented AI-driven insurance document ingestion (>95% accuracy with 1–3 samples) and led Azure-based backend/service development while managing up to 15 engineers at a commercial P&C MGA that reached a ~$60M book of business (~30 loss ratio) before run-off due to paper issues. Known for hands-on discovery (including field inspections) and rapid MVP delivery, including a risk-inspection iPad app that auto-generated draft reports.”

“Full-stack Java developer with IBM and Epic Systems experience modernizing legacy enterprise apps into microservices and delivering customer-facing healthcare claims workflows at very high scale (2M+ transactions/day). Strong blend of product engineering (APIs + React/TypeScript UI) and production operations on AWS, including performance incident remediation via query optimization, indexing, and autoscaling.”

“Senior technology/executive leader with 30+ years building and scaling mission-critical platforms across blockchain, cloud, cybersecurity, and fintech, including leading 100+ person global teams and managing $100M P&Ls. Founded Pharus (2022) after driving Web2-to-Web3/DeFi/metaverse initiatives at SDK Co, using a first-principles, PoC-driven approach to deliver secure, compliance-aware transformations (GDPR/NYDFS) and multi-million-dollar optimizations, with a focus on quantum-resistant Web3 and ethical AI governance.”

“Built a production internal LLM-powered knowledge assistant using a RAG architecture (Python, LLM APIs, cloud services) that answers employee questions with sourced, grounded responses from internal documents. Demonstrates strong practical depth in retrieval tuning (chunking/metadata filters), orchestration with LangChain, and production reliability practices (latency optimization, automated embedding refresh, evaluation metrics, logging/monitoring) while partnering closely with non-technical operations teams.”

Jaideep bommidi

Screened

Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps

Denton, TX8y exp

“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”

Sai Vamsi

Screened

Mid-Level Software Engineer specializing in backend microservices and cloud-native systems

TX, USA4y exp

“ServiceNow engineer who built an AI-powered ticket summarizer end-to-end (RAG with vector DB + GPT, Redis latency optimizations, fallback summarization, and a React UI widget for agent feedback). Also has hands-on ROS 2 experience building real-time sensor-fusion nodes (LiDAR/IMU), debugging SLAM/navigation issues via rosbag + EKF tuning, and bridging heterogeneous robots by translating ROS 2 topics to MQTT/JSON. Strong DevOps background with Docker, Jenkins CI/CD, and Kubernetes orchestration for scalable deployments.”

Mike Khorrami

Screened

Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms

Woodland Hills, CA25y exp

“Engineering leader/player-coach who modernized a legacy C#/SQL Server system to Snowflake + Python on GCP, enabling ~30x scale and supporting hundreds of millions of transactions per day per customer. Strong in architecture tradeoffs (Snowflake vs Databricks), production reliability (New Relic, logging/alerting), and lightweight process improvements like a rigorous Definition of Done and structured PR reviews.”

“Built an LLM-powered customer segmentation agent during a Chewy internship, consolidating Snowflake data into a knowledge graph so non-technical marketing users could query customer cohorts in natural language. Stands out for combining agent/tooling design with rigorous data engineering practices, including schema audits, imputation, validation layers, and idempotent pipelines on messy large-scale datasets.”

“Backend engineer with experience spanning regulated financial systems at Oracle Financial Services and early-stage product building at Apli.ai. Has owned production onboarding infrastructure end-to-end, improved reliability through strong observability and incident response, and also built AI-backed backend workflows using AWS, Bedrock, and RAG.”

“Software developer who uses AI pragmatically across the full stack to accelerate coding, testing, debugging, and documentation while maintaining strong human oversight. Stands out for treating AI output like any other code source—reviewing for architecture fit, security risks, performance, and standards before integration—and for coordinating multiple AI tools across backend, frontend, and test workflows.”

“Full-stack engineer who owned an enterprise AI agent automation platform at KeyBank, building React/TypeScript interfaces and Python/AWS microservices for document-heavy business workflows. Stands out for translating complex AI automation into usable products for non-technical users, with reported productivity gains of about 35% and reduced manual processing.”

“Engineer with experience in small, high-pressure innovation environments and enterprise healthcare platforms, spanning distributed systems, search, and database optimization. At RJ Lee Group, he helped pivot an Air Force document-processing platform from Pig/MapReduce to Apache Storm, enabling near-real-time results, and also built a full-stack natural-language search application that cut analyst investigations from months to weeks or days.”

“Built an agentic medical coding system at Optum that combined LangGraph, LangChain RAG, Azure OpenAI, pgvector, and TypeScript to automate routine clinical coding while escalating risky cases to humans. The system automated about 40% of routine cases at roughly 92% accuracy, with strong production evals and observability using MLflow, Ragas, and DeepEval.”

“Backend/platform engineer from Dune Security with strong experience turning messy, fragmented workflows into reusable production systems. They’ve built a shared database abstraction layer, integrated multiple enterprise security platforms into a unified workflow, and shipped AWS Bedrock-powered security insight features with guardrails and human review.”

“Full-stack engineer who built an internal user-activity tracking and reporting system end-to-end using React/TypeScript, Node/Express, and Postgres, deployed on AWS (EC2/ALB, S3/CloudFront) with CloudWatch observability. Emphasizes reliability and data correctness via idempotent ingestion, retries with exponential backoff, backfills/reconciliation, and performance tuning as data scales, and has experience shipping quickly in ambiguous early-stage startup conditions.”

“Backend/AI workflow engineer with experience at AirKitchenz, Uber, and Vivma Software, building production systems on AWS (Lambda, DynamoDB, Step Functions). Has a track record of major performance wins (DynamoDB latency 2s to <150ms; Postgres query 2s to ~180ms) and shipping LLM-powered onboarding and ticket-routing workflows with strong guardrails (schema validation, confidence thresholds, human-in-the-loop escalation).”

Rushir Bhavsar

Screened

Intern AI/ML Engineer specializing in LLMs, MLOps, and distributed training

1y exp

“Founding AI engineer (June 2024) at Talon Labs who built and productionized an LLM-powered chatbot for interacting with proprietary supply-chain documents, deployed at large scale (25–100,000 users). Experienced with RAG/LLM orchestration (LangChain, LlamaIndex, Groq AI) and production ops tooling (Kubernetes, Docker, Kubeflow, Airflow), with a metrics-driven approach to evaluation, observability, and stakeholder alignment.”

Tuukka Luolamo

Screened

Executive Technology Leader (CTO) specializing in AI, cloud, and distributed platforms

Remote14y exp

“Engineering leader who stays hands-on in high-leverage technical areas (architecture, scalability, reliability) while operating at an executive level. Led StagePilot’s shift from a tightly coupled legacy system to a cloud-native, event-driven real-time platform proven at 1M+ concurrent users, and previously scaled multiple SRE teams at McGraw-Hill with SLOs, on-call, and blameless ops practices.”