Vetted Alerting Professionals

“Full-stack/ML-leaning engineer who has shipped production-grade real-time analytics and an internal AI support assistant using RAG over enterprise documentation. Demonstrates strong systems thinking across scalability, reliability, observability, and LLM safety/evaluation (thresholded retrieval, RBAC, response validation, regression-gated evals), with concrete iteration based on performance metrics and user feedback.”

Richa Jindal

Screened

Senior Product Manager specializing in SaaS CRM, MarTech, and GenAI products

India8y exp

“Product/LiveOps leader who applies free-to-play mechanics to live consumer products; led monetization and engagement for Pavo (video-based Gen Z dating app on iOS/Android), addressing weak D7 retention and low free-to-paid conversion. Implemented progression, nudges, soft paywalls, experimentation, and real-time moderation, driving 3.2x DAU and ~60% lift in early engagement while improving conversion without harming retention.”

JUNG NO

Screened

Senior Solutions Engineer & Applied AI Builder specializing in agentic workflows

Remote, US9y exp

“Built and shipped a production AI booking/quoting system for a Spanish-speaking cleaning business serving English-speaking customers, covering the full booking and payment flow and generating bilingual SEO/AEO content. Uses Gemini/Genkit with multi-agent orchestration (ADK/MCP, LangChain) and a production stack on Vertex AI + Cloud Run + Terraform, with analytics wired from Google Analytics to BigQuery for measurable agent performance.”

“Senior engineer with experience at Micro Focus/HPE (now OpenText) supporting enterprise customers on monitoring platform deployments, upgrades, and ongoing product use. Brings hands-on expertise in operations agents, agentless integrations, security-related upgrade troubleshooting, and cross-functional escalation with engineering to keep customer environments stable and successful.”

“Backend-focused engineer with experience at Ramp, Easebuzz, and George Mason University, spanning data pipelines, workflow automation, and production reliability. Stands out for quantifiable performance gains, strong debugging instincts in distributed job systems, and translating ambiguous finance operations processes into measurable automation outcomes.”

Keeravani Chekuri

Screened

Mid-level AI/ML Engineer specializing in LLM systems and MLOps

Boston, MA3y exp

“Built and deployed an AI tutoring assistant end-to-end at Nexora School, spanning discovery with school districts, multi-agent LangGraph/RAG architecture, AWS Bedrock migration, and post-launch stabilization. Stands out for combining hands-on LLM systems engineering with strong educator-facing trust building, FERPA-driven architecture decisions, and disciplined production practices around evals, logging, and messy document ingestion.”

“Full-stack engineer who built a multi-tenant SaaS analytics dashboard end-to-end with Next.js App Router/TypeScript, emphasizing server components + React Query for performance and real-time UX. Demonstrated strong production ownership post-launch (observability, DB/query tuning, caching strategy) and has concrete wins like 30–40% load-time reduction and Postgres query latency cut to under 200ms.”

“Full-stack engineer with strong DevOps/AWS experience who ships end-to-end React/TypeScript + Node/Python systems and operates them in production. Built an LLM-assisted recommendations workflow for a SaaS product with robust reliability controls (schema-validated JSON outputs, fallbacks, caching, monitoring) and measured impact via adoption, time saved, and override rates; also experienced delivering MVPs fast in early-stage startup ambiguity.”

“Built and deployed production NLP/LLM systems including a multilingual (5-language) health misinformation detection pipeline with latency optimization (batching/quantization/caching) and explainability (gradient-based attention visualizations). Experienced orchestrating end-to-end AI workflows with Airflow and Prefect, and partnering with customer support ops to deliver an AI agent for ticket summarization and priority classification with clear, measurable acceptance criteria.”

“Application security and customer-facing delivery professional with deep experience in eCourt/public portal modernization, protecting sealed records and PII under statutory constraints. Has led threat modeling, phased remediation/risk acceptance to hit legislatively mandated launch dates, and implemented SAST/DAST/SCA programs in CI/CD on AWS/EKS with strong observability-driven troubleshooting and stakeholder alignment.”

“JavaScript engineer with open-source experience on a database visualization library, focused on real-time rendering performance for large datasets (virtualized DOM rendering, requestAnimationFrame/debouncing, memoization) and on raising project quality via tests and CI performance benchmarks. Also built Kafka-based messaging documentation and sample producer/consumer apps to speed onboarding, and has experience diagnosing production issues including concurrency-related duplicate data problems.”

Aneri Patel

Screened

Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval

Washington, D.C.2y exp

“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”

Sai Harsha Kurapati

Screened

Mid-level Backend Engineer specializing in distributed systems and industrial IoT

Indianapolis, IN4y exp

“Backend/Python engineer focused on real-time sensor/IoT analytics: built dashboards and a high-throughput ingestion pipeline (MQTT -> Python worker -> TimescaleDB) with buffering, batch inserts, and validation. Strong Kubernetes + GitOps practitioner (Dockerized microservices, HPA, probes, ArgoCD) who has handled production incidents like CrashLoopBackOff under peak load and supported an on-prem analytics migration to AWS using shadow traffic and rollback plans.”

Anita Bhagashetti

Screened

Mid-Level Software Engineer specializing in distributed systems and cloud microservices

3y exp

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”

hetvi patel

Screened

Mid-level Software/Data Engineer specializing in cloud ETL pipelines and data infrastructure

New Jersey5y exp

“Backend/data engineer who built a production analytics data service (Python/FastAPI on AWS/Postgres with PySpark ETL) handling millions of records per day and drove major latency improvements (10–15s to <2s) via indexing, Redis caching, and shifting aggregations into ETL. Also shipped an LLM-based natural-language-to-SQL assistant end-to-end with strong guardrails (schema restrictions, read-only validation, RBAC, masking) and designed a multi-step agent workflow with verification and fallback logic.”

“Data engineer who has owned high-volume production pipelines end-to-end (200–300 GB/day) on AWS, implementing strong data quality/observability and achieving 99.9% reliability while cutting data issues ~33%. Also built a large-scale external data collection system ingesting millions of records/day with anti-bot/rate-limit handling and backfill tooling, and shipped a versioned REST service exposing curated Snowflake data to downstream teams.”

“Bootstrapped founder of FAMRO LLC with 15+ years spanning startups and corporate roles, including COO experience at an AI/ML startup that built a retail marketing analytics product using camera feeds. Also worked on a clean-tech venture, EnerIO, which won 1st position from Pakistan and was invited to pitch at the GCIP/GEF event in San Francisco in 2015.”