Vetted Apache Kafka Professionals

“Built a production LLM-powered root cause analysis agent for supply chain alerts that helped operations managers avoid manual dashboard investigation. Demonstrates unusually strong depth in agent reliability, orchestration, and observability, with concrete production practices like hallucination blocking, shadow testing on 500 cases, and data-driven improvements that raised user agreement to 94% while cutting GPT-4 usage by 60%.”

“Backend-focused engineer with Walmart Global Tech experience building shipment and seller workflow systems using Spring Boot, GraphQL, Kafka, and async processing. Stands out for improving bulk label API performance by 60-75%, designing item-level partial-failure workflows that improved user clarity, and also exploring AI-powered debugging/RCA platforms with Java, Python, LangChain, and LLM integrations.”

“Backend/data engineer with experience at Nike building high-volume order orchestration and validation APIs using FastAPI microservices on AWS EKS with Kafka, Redis, and Postgres. Strong in production reliability (timeouts/retries/idempotency), GitOps (Argo CD) + Terraform deployments, and data pipelines (AWS Glue/S3), with hands-on incident ownership and legacy modernization into API-driven services.”

“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”

“LLMOps-focused technical leader who took an LLM use case from prototype to production for a non-technical customer by combining trust-building and structured enablement with a robust AWS/Kubernetes-based MLOps stack. Built observability and rollback mechanisms (Grafana + MLflow) to troubleshoot in real time, and scaled delivery by hiring a 5-person team while partnering with sales to manage expectations and drive adoption across departments.”

“Player-coach engineering leader focused on scalable data security scanning and risk detection in hybrid cloud, owning architecture and core implementation of an incremental/parallel DSPM scanning engine. Shipped production improvements including 60% lower scan latency and 30% fewer false positives, with strong emphasis on correctness under concurrency, multi-tenant observability (SLOs/burn-rate alerts), and disciplined rollout practices (feature flags, shadow scans, canaries).”

Sujit Singh

Screened

Engineering Director specializing in backend & data platforms for enterprise SaaS and cybersecurity

San Jose, CA21y exp

“Backend/data engineering player-coach on a UEBA cloud security analytics platform who standardized MLOps and detection development for 180+ detections, cutting ship time from 6–7 weeks to ~3 weeks while reducing false positives. Proven at operating large-scale streaming + Spark systems (200K+ events/sec, 100+ TB/day), driving major reliability/cost improvements, and leading incident response and team execution through GA.”

“Software engineer with experience across early-stage startups and production full-stack systems, including migration work from a Go monolith to a Node.js backend and a clinical research application deployed on Kubernetes in AWS. Has worked across Go, Python, JavaScript/TypeScript, React, SQL databases, and B2B SaaS data-streaming products.”

“Engineering leader (ActiveCampaign, Yalo) with a track record of scaling both systems and orgs: grew an engineering team from 90+ to 200+ (30+ scrum teams) while re-architecting a marketing automation platform from batch to near real-time. Led major infrastructure shifts (RabbitMQ to Kafka, multi-region redundancy) and reports outcomes including 600%+ throughput gains, 99.99% uptime, and business growth from ~80K to 185K customers with revenue surpassing $200M over ~3 years.”

Kusumita Dasgupta

Screened

Director-level Engineering Leader specializing in data platforms, cloud systems, and LLM products

United States22y exp

“Engineering leader/player-coach with recent hands-on work delivering an agentic AI MVP on Amazon Bedrock (conversational UI + supervisor agent routing between internal knowledge and external sources). Previously drove large-scale data platform cost optimization at Twitter, saving ~$3M–$5M annually, and has owned production incidents end-to-end with a focus on analytics/monitoring improvements and team coaching.”

“Senior engineering leader with a rare blend of deep platform/infrastructure expertise and large-scale people leadership, spanning hands-on cloud-native architecture through management of globally distributed organizations of up to roughly 180 engineers. Particularly strong in Kubernetes platform modernization, reliability engineering, and scaling high-throughput SaaS systems while aligning platform investments to customer and business outcomes.”

Xun He

Screened

Staff Software Engineer specializing in backend systems and security engineering

25y exp

“Senior backend/infrastructure engineer with experience at Microsoft, DocuSign, Pinterest, and Harness, focused on security and developer productivity systems. Stands out for building Pinterest's first vulnerability management platform from scratch for a 100,000-EC2 production environment and driving major performance gains, while also delivering CI/Docker infrastructure and Python test intelligence features shaped by customer demand.”

“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”

“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”

Jun Ouyang

Screened

Principal Software Engineer / Tech Lead specializing in distributed systems, payments, and reliability

San Francisco, CA20y exp

“Backend engineer with DoorDash experience building production-critical systems spanning LLM-based real-time safety moderation (SendBird callbacks + ChatGPT risk scoring with automated actions) and large-scale payments data pipelines (Kafka to CockroachDB with aggregation APIs). Also led cross-team reliability work to standardize SLOs and drove an incident redesign from batch pull to real-time push callbacks to eliminate critical-event latency.”