Vetted Elasticsearch Professionals

“ML/AI engineer with hands-on ownership of production document intelligence and GenAI systems, spanning model experimentation, AWS deployment, monitoring, and iterative optimization. Stands out for turning document-heavy workflows into reliable, near real-time products with measurable gains in accuracy, latency, and manual-effort reduction, while also shipping citation-grounded RAG features that drove user trust and adoption.”

Harsh Sanas

Screened

Intern Full-Stack Engineer specializing in AI and distributed systems

Los Angeles, CA2y exp

“Full-stack product engineer who has designed and shipped production web experiences in EV charging, trading, automotive companion apps, and AI systems. Stands out for owning user-facing React experiences through backend integration and production monitoring, with a strong bias toward reliability in real-time and high-stakes workflows. Also has early-stage Scale AI experience building a Text-to-SQL agent stack with Python, PostgreSQL, Redis, Kafka, and AWS.”

Darsh Sharma

Screened

Mid-level Software Engineer specializing in ML systems and microservices

Madison, WI2y exp

“Teradata Text Security intern who built a production LLM-powered planner agent that decomposes complex tasks into dependency-aware subtasks (DAG/topological graph) and executes them via a custom orchestrator with parallelism, status tracking, and error handling. Also contributed to an HR-facing internal document chatbot concept to streamline onboarding, showing cross-functional collaboration.”

Kaustubh Rai

Screened

Junior Software Engineer specializing in scalable distributed systems and cloud platforms

Pittsburgh, PA2y exp

“Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.”

Nilesh Dixit

Screened

Executive AI engineering leader specializing in agentic AI and enterprise platforms

San Francisco, CA24y exp

“Bay Area engineering leader and startup co-founder with a rare mix of deep hands-on architecture experience, large-scale people leadership, and cross-functional product ownership. He helped launch GE Digital's industrial IoT efforts, holds multiple patents in the space, has scaled teams to 60-70 people, and has led both enterprise platform modernization and AI startup product development.”

“Healthcare-focused full-stack/platform engineer with recent hands-on experience in Go, React, Python, Kubernetes, and AWS. They have worked in high-reliability, compliance-heavy environments, driving infrastructure modernization, internal operational tooling, and observability improvements that reduced troubleshooting friction for clinician platform and support teams.”

“SRE-focused engineer with experience at Sony Interactive Entertainment productionizing high-throughput LLM/agentic systems on Kubernetes, including GPU-aware autoscaling and warm-pool strategies to manage latency and cost under traffic spikes. Demonstrates strong incident response using Prometheus/Grafana + Jaeger tracing (e.g., resolving recursive agent loops and restoring 99.9% availability within minutes) and partners closely with sales/customer teams through PoV demos and developer workshops.”

Paiman Nodoushani

Screened

Executive CTO specializing in AI-powered transformation for enterprise SaaS

New York, NY35y exp

“Former Cisco professional who successfully pitched and got funding for adding virtualization to access routers to enable third-party application development, framing the opportunity with clear revenue upside and risk management. Highly interested in AI—especially agent-based development—and believes it lowers the barrier to building and shipping new products with small, high-caliber teams.”

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp

“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”

Pranav Puranik

Screened

Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP

Austin, TX5y exp

“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”

“Senior full-stack engineer with seed-stage fintech experience who has led payment API development, implemented compliance-related standards, and built production systems across React, Go, Python, Node.js, and PostgreSQL. Notable impact includes enabling a first major client launch, reducing logistics response times by 30%, improving page load times by 40%+, and cutting analytics report generation from minutes to seconds.”

“Full-stack engineer with strong AI systems and B2B SaaS experience across BrightOps, Zapier, Nordstrom, and Calendly. They’ve owned architecture for an AI-powered tutoring platform, improved retrieval quality with a hybrid vector-plus-keyword approach, and built Go services processing over 1 million student events per day. Particularly compelling for teams building data-intensive, reliability-critical products with LLM, workflow automation, or compliance-oriented use cases.”

“Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.”

“Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.”

“IBM engineer who shipped an LLM-powered knowledge transfer platform (Transition Engine) for federal contract handoffs, deployed on a production OpenShift cluster in AWS GovCloud with FedRAMP-aligned compliance and strict data-boundary constraints. Led retrieval strategy, prompt engineering, and production deployment (PostgreSQL/Milvus/Keycloak), driving a reported 50% reduction in contract transition ramp-up time and positioning the tool for revenue-critical federal deals.”

“Engineer with hands-on experience shipping production Python integrations and designing for reliability from day one, including idempotency, retries, dead-letter handling, contract checks, and full observability. Also brings web automation experience with Puppeteer and has implemented high-availability failover using load balancer liveness checks, backup environments, and cold standby architecture.”

Christopher Kirby

Screened

Executive engineering leader specializing in platform engineering, AI systems, and SaaS

Detroit, MI24y exp

“Senior engineering executive who has repeatedly rebuilt and scaled product engineering organizations in high-growth environments, including restarting Rocket Auto’s stack from scratch and hiring 100+ engineers during StockX’s hypergrowth phase. Particularly differentiated by being unusually hands-on for an executive leader, with active open source work and a strong focus on AI-native engineering workflows, developer automation, and modern architecture transformation.”