Vetted Apache Kafka Professionals

“Backend engineer with experience at JPMorgan Chase and Walgreens, owning transaction-processing and prescription data flow systems in regulated environments. Brings strong hands-on depth in Spring Boot microservices, Kafka, Redis, Kubernetes, observability, and production incident resolution, plus practical experience integrating OpenAI-powered workflows with validation and fallback safeguards.”

“Backend/full-stack engineer (5+ years) with Shopify experience integrating LLM/RAG workflows into production APIs. Owned a Python TensorFlow Serving inference pipeline connected to Java microservices via gRPC, optimizing tail latency at ~10k concurrent load and improving retrieval relevance with embedding and evaluation work. Strong Kubernetes/EKS + GitOps/CI/CD background, including monolith-to-microservices migrations and event-driven streaming patterns.”

“Backend/platform engineer with deep payments experience who built and operated a real-time transaction routing service end-to-end on AWS (Spring Boot, PostgreSQL/RDS, Redis, Kubernetes), delivering ~40% latency reduction and 99.99% uptime via strong resiliency and observability practices. Also productionized an internal LLM-powered RAG knowledge assistant with guardrails and a user-feedback-driven evaluation loop, and has led incremental monolith-to-microservices modernization using Strangler Fig and shadow traffic.”

Shuju Sun

Screened

Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment

PA, USA4y exp

“Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).”

William Elderton

Screened

Executive technology leader specializing in FinTech, cloud platforms, and digital transformation

Austin, TX26y exp

“Seasoned operator with 30 years of experience at multiple startup companies, primarily in venture-backed environments, plus some exposure to private equity-backed firms. The candidate is highly familiar with the VC and accelerator ecosystem, though they clarified they were pursuing a CTO role rather than actively planning to found a startup.”

“ML/GenAI engineer with strong end-to-end production ownership across predictive ML, RAG systems, and LLM routing. They pair solid platform engineering skills with measurable business impact, including 15% churn reduction, 35% support ticket deflection, 45% GenAI cost savings, and a shared inference library that cut deployment time from weeks to days.”

“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.”

Michael Matonte

Screened

Senior Backend Engineer specializing in distributed systems and AI-enabled platforms

Jersey City, NJ7y exp

“Backend engineer with end-to-end ownership experience in high-stakes environments spanning Citibank and industrial operations. They built an internal banking platform that automated complex entitlement workflows across thousands of business units with an 80% reduction in redundant processing, and they are now applying AI through OpenAI-powered agent workflows with RAG, vector databases, and security controls.”

“Engineering leader focused on large-scale enterprise SaaS and MDM platforms, with experience modernizing monoliths into microservices, improving reliability, and scaling systems to support 15M devices across AWS and Azure. Stands out for combining deep platform architecture work with strong org-building: managed teams up to 45 globally and built a 0-to-1 platform services team to 22 people in under a year.”

Sarthak Gupta

Screened

Mid-level AI/ML Engineer specializing in LLMs, NLP, and real-time AI systems

New York, NY4y exp

“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”

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.”

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.”

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.”

“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.”

“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Data engineer at Plaid who built greenfield, end-to-end real-time transaction pipelines and FastAPI data services for fraud detection and analytics, handling millions of events per day. Strong focus on reliability and data integrity via Great Expectations validation, Airflow-based monitoring/SLAs, quarantine/staging patterns, and robust external data ingestion with schema versioning and backfills (reported 50% fewer anomalies and ~40% fewer failures).”

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.”

Feras Alsaiari

Screened

Senior Software Engineer specializing in AWS data platforms and event-driven systems

4y exp

“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”

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).”

“Backend-focused engineer who uses AI pragmatically as a force multiplier rather than a substitute for engineering judgment. They stand out for applying structured, agent-style workflows to code generation, debugging, and production log analysis while maintaining strong emphasis on correctness, performance, and reliability in backend and microservices environments.”

“Built and architected ML-integrated payment processing systems for PlayStation at Sony Interactive Entertainment, covering fraud determination, provider routing optimization, and model-training feedback loops in production. Brings a strong reliability and observability mindset, with concrete experience designing fallbacks, retries, correlation-ID tracing, and statistically grounded evaluation for non-deterministic systems.”

Rediet Gesesse

Screened

Mid-level Software Engineer specializing in FinTech and full-stack platforms

San Francisco, CA4y exp

“Built a kitchen capacity management system for merchants, owning deployment through stabilization and continuously tuning capacity based on fulfillment and cancellation outcomes. Also designed customer-support decision workflows for refunds/credits with a focus on fraud cost reduction, and has hands-on experience with Kafka, Flink, relational databases, and production incident mitigation via feature-flag rollbacks.”