Vetted Observability Professionals

Priyank Jhaveri

Screened ReferencesModerate rec.

Junior AI/ML & Mobile Engineer specializing in LLMs, synthetic data, and React Native

New York, United States1y exp

“Currently at Uplift AI shipping production LLM features that generate personalized growth insights from user reflections using BERT + embeddings + RAG, with strong safety/guardrail practices for sensitive contexts. Also built an end-to-end React Native UGC challenge submission/moderation system that improved repeat submissions and 7-day retention, and has applied rigorous clinical-style evaluation methods on a dental X-ray disease detection project to reduce false negatives.”

Mudit Devenkumar Choksi

Screened ReferencesModerate rec.

Junior Full-Stack Software Engineer specializing in web apps, automation, and cloud systems

Louisville, KY2y exp

“Engineer with hands-on experience owning end-to-end industrial automation deployments and real-time data systems. Most notably led a multi-million dollar warehouse automation implementation that reduced manual intervention by 25%, while also building streaming text analytics pipelines and strengthening production reliability through robust observability and pipeline controls.”

“Backend engineer focused on real-time, event-driven distributed systems (Node.js/TypeScript) with strict latency and reliability requirements. Deep hands-on experience debugging concurrency issues and designing resilient workflows (idempotency, circuit breakers, compensating actions) with strong observability; familiar with ROS/ROS2 concepts and confident ramping into robotics integrations.”

“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”

“Built and productionized an LLM-enhanced version of the WeDAA platform to auto-generate microservice architecture diagrams and support code generation from user prompts, including a practical solution for non-overlapping canvas object placement via coordinate templates. Experienced in diagnosing agentic workflow failures using AWS Strands agents with feature-flagged debug logging, and frequently supports sales through tailored demos and POCs to drive adoption.”

“Built and deployed a production LLM-assisted recommendation and insights platform that unifies structured, semi-structured, and unstructured data via a modular ingestion pipeline, canonical schemas, embeddings, and late-fusion modeling. Experienced in operationalizing ML/LLM systems with Airflow and Kubernetes (Dockerized services, autoscaling, rolling updates) and emphasizes reliability through layered testing, guardrails, monitoring, and A/B experimentation while partnering closely with non-technical stakeholders.”

“Built and deployed an LLM product called "Content Craft" combining BART-based summarization with a RAG Q&A chatbot using LangChain, embeddings, and a vector database. Has hands-on MLOps experience containerizing and serving models with FastAPI and running them on Kubernetes with monitoring, self-healing, and autoscaling, and has practical experience reducing hallucinations through structured prompting.”

“Built and productionized an LLM-based appointment management agent, implementing RAG with Redis and LangGraph plus multi-agent intent handling and rule-based conflict guardrails to prevent double-booking under high load. Experienced in real-time diagnosis of agentic workflow failures using logs/traces and state inspection, and in driving adoption via interactive developer demos and sales-aligned custom customer scenarios.”

“Software engineer with enterprise CPQ/CRM/ERP integration experience (Argano) who owned an end-to-end pricing preview capability deployed on AWS Kubernetes with Jenkins CI/CD and full observability (Prometheus/Grafana). Also built an AI-native research agent using LangChain + Chroma to filter academic papers, reporting ~15 hours/week saved for a professor.”

“Data/ML platform engineer with ~6 years in financial services and enterprise data platforms, building regulated fraud/credit-risk pipelines on AWS (Airflow, EMR/Spark, MLflow) and an Azure lakehouse ingesting 50+ sources and serving ~100M records/day. Also led an early-stage deployment of a RAG-based internal AI search tool using AWS Bedrock and LangChain with automated evaluation to validate LLM accuracy.”

Sneha Sridhar

Screened

Mid-level Software Engineer specializing in cloud-native backend and distributed systems

Remote, USA4y exp

“Backend/full-stack engineer with experience building customer-facing contact-center automation (agent assignment) and internal editorial/data operations APIs for life-sciences ontology management. Strong in microservices and event-driven systems (Spring Boot + Kafka), third-party integrations (Genesys/Five9), and pragmatic iteration via MVP scoping, tight stakeholder demos, and observability-focused reliability.”

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.”

Jaxon Repp

Screened

Executive Technology Leader specializing in distributed systems and multi-cloud infrastructure

Denver, Colorado, United States9y exp

“Early-stage builder who blends deep technical product work with go-to-market execution: created developer-focused platform tooling (Rust/Node/React) and at Harper moved from customer success into sales/partnerships, leading an Akamai partnership that ultimately helped close Walmart. Currently building a distributed application platform in Rust and iterating on macro-based abstractions to make Rust feel as approachable as Node.js; has not yet closed a seed round and is seeking a trusted operator counterpart.”

Monish Reddy Bonthu

Screened

Mid-Level Full-Stack Engineer specializing in real-time systems and FinTech

FL, USA5y exp

“Backend engineer with hands-on experience modernizing a real-time logistics/tracking platform from a tightly coupled polling architecture to a service-oriented/microservices design using Node.js and WebSockets. Emphasizes contract-first FastAPI development, defense-in-depth security (JWT/OAuth, RLS/Supabase), and safe incremental migrations with feature flags and strong observability, delivering sub-second updates and improved performance under peak load.”

Leon Hsi

Screened

Mid-level Solutions Consultant / Full-Stack Developer specializing in APIs, SQL, and cloud systems

Houston, TX4y exp

“Builder with hands-on security hygiene experience from developing a helpdesk portal handling sensitive payment/invoice data, focusing on RBAC, least-privilege integrations (QuickBooks/Atera), and tightening API authorization to prevent cross-account access. Also built personal projects integrating Twilio/Callkeep/Supabase/OpenAI with strong key management and defensive handling of real-world API/network failure modes; holds an ISC2 certification and is actively deepening cloud security skills.”

Yuhao Lin

Screened

Junior Full-Stack Software Engineer specializing in web platforms and cloud-based systems

Boulder, CO1y exp

“Full-stack engineer with hands-on document extraction experience: built an end-to-end handwritten OCR pipeline using OpenCV + EasyOCR with spellcheck post-processing and a Tkinter-based manual correction workflow. Also brings practical distributed-systems and e-commerce reliability experience (REST orchestration, retries, logging, Stripe idempotency), and is candid about not yet shipping LLM agents to production.”

“Independent builder of production-grade systems: shipped an end-to-end URL shortener with JWT auth, Redis rate limiting/caching, Postgres, Docker, and real-time analytics, and separately architected a Redis-backed distributed task queue handling 1000+ tasks/min. Demonstrates strong distributed-systems instincts (atomicity, retries/DLQ, idempotency, heartbeats) plus a focus on maintainable code and self-documenting APIs (FastAPI/OpenAPI, versioned routes).”

“Backend/AI engineer who built production-grade intelligence systems in high-stakes domains including tax/legal document analysis and brain tumor MRI workflows. Stands out for combining LLM/RAG product delivery with strong engineering rigor around retrieval evaluation, grounding, validation, observability, and safe fallbacks—turning impressive demos into systems users could actually trust.”

“Built a production ad-spend optimization system that combined deterministic audit logic with LLM-generated explanations, surfacing severe inefficiencies including 70-90% wasted spend in some Google Ads accounts. Stands out for pairing measurable business impact with pragmatic AI safety and usability decisions, including approval-gated execution and structured, human-readable recommendations.”

“Frontend-leaning full-stack engineer who has rebuilt a high-volume order management system in Next.js/TypeScript for 6000+ active orders and also owned end-to-end product/data architecture in Firebase/Firestore. Stands out for strong performance instincts, type-safe frontend architecture, and pragmatic 0→1 execution across UI, APIs, and data pipelines.”

Yatin Rajkumar Kalra

Screened

Senior Full-Stack Engineer specializing in cloud-native AI and Healthcare IT

Remote6y exp

“Built AIO, a 7-agent system that automatically fixes failed GitLab CI/CD pipelines in under 60 seconds using Redis queues, typed TypeScript contracts, and strong observability. Heavy AI user who still applies rigorous human review for logic, security, scalability, and code quality, and has made deliberate architectural choices rather than relying blindly on frameworks.”

Victor Iagnov

Screened

Executive engineering leader specializing in SaaS platforms and AI-enabled architecture

Windermere, FL9y exp

“Engineering executive and former CTO of 3DWORLD who helped scale the business through roughly 22x revenue growth and 15x customer growth over four years while building a 20+ remote cross-functional org. Unusually for a senior leader, they remain hands-on in architecture and production debugging, with recent depth in AI-powered support systems, retrieval-based knowledge workflows, and scalable full-stack platform design.”

“Full-stack engineer with hands-on ownership of a production cart-audit workflow redesign, spanning schema redesign, Rails APIs, and frontend navigation for non-technical operations users. Particularly strong in modernizing legacy systems safely with rollback paths and clearer data relationships, while also building AI-powered side projects using Flask, LangChain, and GPT for GitHub code analysis.”

Baljinnyam Puntsagnorov

Screened

Mid-level Full-Stack AI Engineer specializing in agentic AI and FinTech systems

Bellevue, WA3y exp

“Full-stack and AI systems engineer with a strong track record in high-stakes workflow automation and payments reliability. They’ve built production LLM systems with retrieval, validation, evals, and human-in-the-loop controls, while also shipping payment infrastructure that eliminated duplicate payouts/charges and supported 8,000+ daily transactions at 99.95% uptime.”