Vetted Observability Professionals

“Backend engineer with experience building and modernizing high-volume healthcare transaction systems, including migrating Java services to Spring Boot microservices and adopting Kafka-based event-driven architectures. Strong focus on production reliability and operability (observability, CI/CD, standardized patterns) plus security (OAuth/JWT, RBAC, Postgres/Supabase RLS) and resilient stream processing (idempotency, DLQs).”

“Frontend engineer at Mailchimp who leads end-to-end React/TypeScript features on the in-app homepage, including onboarding and campaign discovery components. Demonstrated measurable performance impact by cutting homepage LCP by ~2.5s and successfully shipped a major feature on an accelerated deadline using structured QA and staged rollout.”

“ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).”

“LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.”

“Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).”

“LLM/agentic workflow specialist with healthcare deployment experience who has taken LLM-based automation from prototype to production using operator-in-the-loop validation, RAG-style retrieval, RBAC, and monitoring for sensitive data compliance. Demonstrated real-time incident resolution (retrieval timeouts due to network/proxy misconfig) and strong GTM support—hands-on developer workshops and sales demos translating technical safeguards and real-time ETL into measurable ROI (70% ops reduction, ~$200K/year savings).”

“LLM/agentic systems practitioner focused on taking customer prototypes to production by hardening reliability (APIs, monitoring, security) and adding guardrails, evals, and incremental rollouts. Experienced diagnosing RAG/agent failures via structured tracing and fixing retrieval-quality issues (freshness checks, filters, schema enforcement). Also supports pre-sales by leading developer demos/workshops and building targeted POCs to address scalability/reliability objections and drive adoption.”

“Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Built and deployed a production LLM system that scraped Google Maps menu photos, extracted structured prices via OpenAI, and cross-validated them against website-scraped data to automate data-quality verification at scale (replacing costly manual contractor checks). Demonstrates strong reliability instincts—precision-first prompting, output gating with image-quality metadata, and fuzzy matching/RAG techniques—plus solid orchestration (Dagster/Airflow) and observability (Sentry, Prometheus/Grafana).”

“Full-stack engineer with strong production ownership across SDK tooling, APIs, and operations. At Statsig, built real-time SDK diagnostics spanning 16 SDKs and improved incident response (40% faster mitigation) with Datadog SLOs/alerting; also shipped an enterprise Console API + interactive OpenAPI-based docs with robust versioning/migration practices. Has early-stage startup experience at Layup Parts, translating AS-9100 compliance needs into production workflows under rapidly changing requirements.”

“Backend-leaning full-stack engineer with production experience in both healthcare (claims enrichment/interoperability at Abacus) and finance (Goldman Sachs pricing/risk APIs + React dashboards). Built an event-driven AI grading platform using Postgres Debezium CDC + Kafka + FastAPI on AWS that cut manual grading ~70% and served 1000+ students, with strong emphasis on reliability, testing, and performance tuning.”

“Currently at Huntington Bank, built a production-grade RAG system that helps business/operations teams get grounded answers from large volumes of internal enterprise documents. Owns ingestion and FastAPI backend, tuned hybrid BM25+vector retrieval and chunking for relevance, and evaluates reliability with metrics and observability (LangSmith, CloudWatch, Prometheus/Grafana) while partnering closely with non-technical stakeholders.”

“Full-stack engineer who built and supported production features in a productivity/task-tracking app using Next.js App Router + TypeScript (server components for initial render, client components for interactivity, API route handlers for mutations). Also designed and optimized Postgres data models/queries and implemented resilient, event-driven payment processing with idempotency, retries, audit logs, and strong testing/observability practices.”

“Cross-functional product/engineering leader with startup and enterprise experience (Whimstay, Wells Fargo, Leap AI Technologies). Has owned end-to-end delivery including UI and payment architecture—built a multi-customer reservation payment flow using pre-auth plus event/timer-driven reminders and handled tricky edge cases like date changeover. Also introduced lightweight process (Jira, sprints, team/module structuring) to increase delivery speed in an early-stage AI document-matching startup.”

“Engineer with production experience in both high-throughput banking risk systems and LLM agent platforms. Built a real-time transaction risk scoring middleware at JPMorgan Chase (1M+ requests/day) emphasizing HA, observability, and audit/PII compliance, and also architected multi-step LLM agents with strict schema-based tool calling, evaluation loops, and safety guardrails for messy enterprise data.”

“Cloud/platform engineer with hands-on ownership of AWS EKS Kubernetes platforms built and upgraded via Terraform, including AWS networking/security, EBS/EFS/S3 storage integration, and reliability validation through CloudWatch plus Prometheus/Grafana. Also has on-prem VMware/vSphere administration experience and day-to-day hybrid on-prem-to-AWS operations (VPN/Direct Connect), with examples of resolving pod instability from an application memory leak and fixing a production connectivity drop via routing/firewall troubleshooting.”

Arjun Masadi

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare platforms

Remote, USA3y exp

“Full-stack engineer (3+ years) who owned an AI-powered customer financial health dashboard end-to-end at Regions Bank, combining React/Java Spring Boot with LangChain + Pinecone for personalized insights. Strong production operations experience on AWS EKS with CI/CD and observability (OpenTelemetry/Prometheus/Grafana), delivering measurable outcomes including 22% support reduction and 99.9% uptime, plus robust third-party financial/clinical integrations.”

Akshay Danthi

Screened

Senior AI Engineer specializing in production GenAI systems

San Francisco, CA8y exp

“AI engineer who has shipped production LLM systems end-to-end, including a natural-language-to-SQL analytics copilot for career advisors that achieved ~95% query success through schema grounding, access controls, and automated regression testing with golden queries. Also builds LangGraph-orchestrated multi-step agents (resume analysis, recommendations) and RAG pipelines (PDF ingestion + FAISS) and partners closely with non-technical users to drive adoption and trust.”

Fnu Pallavi Sharma

Screened

Intern Data Scientist specializing in ML, NLP, and MLOps for healthcare and enterprise AI

Madison, WI1y exp

“Built a production multi-cloud LLM-driven IT ticket automation system using LangGraph, Azure + Pinecone RAG, and an Ollama-hosted LLM on AWS, with Terraform-managed infra and PostgreSQL audit/state tracking for reliability. Also partnered with UW School of Medicine & Public Health students to deliver a glioma survival risk-ranking model, translating clinical feedback into practical pipeline improvements (imputation, site harmonization) and stakeholder-friendly visualizations.”

Ishwari Kulkarni

Screened

Intern IT & Data Analytics professional specializing in automation, cloud operations, and dashboards

Dallas, TX2y exp

“AppSec-focused engineer with experience spanning Accenture and a digital operations support internship, emphasizing secure SDLC and CI/CD security automation (SAST/DAST/SCA). Has hands-on troubleshooting experience using logs/metrics/APM traces (e.g., resolving DAST timeouts caused by rate limiting) and designs AWS/Kubernetes scanning integrations with least-privilege IAM, private networking, secrets management, and observability.”

“Cloud-focused platform/infrastructure engineer centered on AWS and Kubernetes, with hands-on experience building EKS environments via Terraform/Terragrunt, bootstrapping clusters with Cilium and ArgoCD, and integrating persistent storage and backup tooling like EFS/EBS CSI and Velero. While no longer focused on on-prem or hybrid operations, they also bring prior VMware/Hyper-V and migration-to-AWS experience, making them strongest in modern cloud platform engineering roles.”

“JavaScript/React/TypeScript engineer with hands-on open-source experience improving a hooks utility library—fixed a reported async race condition that reduced unexpected re-renders and added a debounced callback hook that became widely used. Brings a production-minded approach to performance and abstractions (APM/metrics-driven, DB/caching focus) with strong testing, documentation, and community support practices.”

Omkar Lahurikar

Screened

Senior engineering founder specializing in AI systems and automotive controls

Dearborn, MI13y exp

“Builder-minded founder/operator currently at Ford who previously co-founded MeruDynamics, an "Uber for manufacturing" platform, and took it from zero to paying customer without raising capital. He also independently built and deployed RDD, an AI copilot for engineering decision capture, with evals, prompt versioning, and LLM cost telemetry—showing unusual depth in both product thinking and practical AI execution.”