Vetted CI/CD Professionals

Nikhil Reddy

Screened

Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms

San Francisco, CA5y exp

“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

Screened

Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants

New York, NY6y exp

“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.”

“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.”

“Technology-first venture builder with strong familiarity in the VC/accelerator landscape, specializing in greenfield innovation, M&A, and large-scale transformation/modernization. Described building a venture-funded retail banking greenfield startup to integrate lending-as-a-service for SME lending while meeting federal and local financial services compliance requirements.”

Christian Alcala

Screened

Mid-level Software Engineer specializing in LLM-powered analytics

Redwood Shores, CA4y exp

“Engineer with a pragmatic, production-focused approach to AI development, emphasizing verification, observability, and system design over hype. Built LLM-driven features and automated regression/validation pipelines, including quality measurement work at Oracle, and uses hands-on projects to test how AI fits into real business workflows.”

Dexin Huang

Screened

Junior AI Engineer specializing in LLM systems, RAG, and full-stack automation

Guilford, CT1y exp

“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.”

Amrita Pritam

Screened

Senior Backend Engineer specializing in distributed microservices and event-driven systems

Fremont, CA10y exp

“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.”

“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.”

“ML/LLM engineer who built a production RAG system (GPT-4 + FAISS + FastAPI) to deliver fast, grounded answers from proprietary documents, optimizing for sub-200ms latency and high-concurrency scale. Strong MLOps/observability background: drift monitoring with Prometheus + Streamlit, automated retraining via Airflow, Kubernetes autoscaling, and MLflow-managed model lifecycle, plus inference cost reduction through quantization and structured pruning.”

“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.”

“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.”

“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.”

Michael Kaufman

Screened

Mid-Level Full-Stack Software Engineer specializing in mobile and web platforms

Seattle, WA5y exp

“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

Screened

Mid-level Software Developer specializing in cloud data engineering and MLOps

NYC, New York3y exp

“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

Screened

Mid-level Frontend Software Engineer specializing in accessible React and Next.js applications

Woodbridge, NJ4y exp

“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

Screened

Executive Technology Leader specializing in Enterprise AI, Cloud Architecture, and Data Platforms

Houston, TX16y exp

“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.”

Estime Aristomene

Screened

Executive CTO specializing in regulated FinTech payments and AML

Dallas, TX21y exp

“Founder of two bootstrapped ventures—Brain Matched, a career tech platform, and AIqorx, a software/infrastructure company. Distinguishes themself as a builder focused on modular, scalable technical infrastructure that reduces technical debt and speeds execution, with a venture-studio mindset around creating shared tech stacks that give portfolio companies an advantage.”

“CTO-level leader with deep insurtech and cloud security/SaaS experience who has repeatedly scaled global engineering orgs and delivered high-velocity roadmaps. Most recently led Delos Insurance Solutions to launch new homeowners programs for wildfire-prone regions every 3–4 weeks while meeting DOI/SLA requirements, driving $135M GWP and $250M capacity and reaching cash-flow positive. Also led major scalability re-architecture at CloudPassage (Postgres to Cassandra + Kafka) and built a large Estonia-based engineering hub at Cybercube.”