Pre-screened and vetted.
Senior Software Engineer specializing in distributed systems and cloud-native platforms
Senior Full-Stack Software Engineer specializing in scalable microservices and cloud platforms
Executive Technology Leader specializing in Cloud, AI/IoT, and Cybersecurity
Mid-level Software Engineer specializing in backend systems, microservices, and AI search
Staff Software Engineer specializing in backend platforms and FinTech/SaaS systems
Principal Software Engineer specializing in platform engineering and distributed systems
Mid-level Software Engineer specializing in cloud-native AI/ML and full-stack systems
Senior Data Engineer specializing in cloud data platforms and real-time streaming for financial services
“Data engineer with experience at Bloomberg, UBS, and Bank of America building high-volume financial data platforms and services. Owned an end-to-end pipeline processing ~150–200M records/day (Kafka/Cassandra/S3 → Spark/PySpark → Snowflake) with strong data quality controls and Airflow reliability practices, reporting ~99% reliability and major performance gains. Also built large-scale external API ingestion with compliance-minded rate limiting, schema versioning, and quarantine/validation layers.”
Junior Full-Stack Developer specializing in Java microservices and cloud platforms
“Full-stack engineer (~2.6 years) with strong Java/Spring Boot backend experience and React/Angular frontend exposure, who has worked on enterprise-scale systems at Dell processing ~1.8M daily transactions/events. Built secure, partner/internal-facing APIs (OAuth2/JWT) across 14 integrations and implemented Kafka-based order/payment workflows with idempotency and sub-700ms processing targets, plus CI/CD and Selenium-based release validation.”
Mid-Level Full-Stack Software Engineer specializing in Java/Spring, React, and AWS
“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.”
Director of Engineering specializing in cloud platforms and enterprise SaaS
“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.”
Director-level engineering leader specializing in identity, authentication, and AI security
“Engineering leader at Intuit focused on identity, authentication, and security infrastructure for AI integrations in highly sensitive financial workflows. Led a 10-person Tier 1 team, built an AgentIdentity framework across 3 organizations, and helped launch TurboTax/QBO integrations with ChatGPT and Claude while maintaining strict reliability and security standards.”
Intern Full-Stack Engineer specializing in AI and distributed systems
“Full-stack product engineer who has designed and shipped production web experiences in EV charging, trading, automotive companion apps, and AI systems. Stands out for owning user-facing React experiences through backend integration and production monitoring, with a strong bias toward reliability in real-time and high-stakes workflows. Also has early-stage Scale AI experience building a Text-to-SQL agent stack with Python, PostgreSQL, Redis, Kafka, and AWS.”
Junior Software Engineer specializing in AI agents, RAG, and full-stack development
“Backend engineer who built and iterated a secure, multi-tenant RAG system over a large document corpus, emphasizing strict RBAC/ACL isolation, hybrid retrieval (vector+keyword), reranking, and strong observability to balance relevance, latency, and cost. Also led production refactors/migrations using strangler + feature flags/dual writes and has experience catching subtle real-world failure modes (including in a sensor calibration optimization pipeline).”
Senior Software Engineer specializing in Python backend systems on AWS
“Backend/data engineer from ASML who modernized a legacy SAS-based statistical processing system into a cloud-native AWS platform (Lambda/FastAPI, Step Functions/EventBridge, Glue, S3/RDS) with strong reliability and data-quality practices. Demonstrated measurable performance wins (RDS query reduced from 90+ seconds to <5 seconds) and hands-on incident ownership for production ETL pipelines.”
Mid-level Full-Stack Software Engineer specializing in cloud-native platforms
“Amazon experience integrating LLM-powered chat automation into Amazon Connect contact-center workflows, taking prototypes to production with compliance-minded guardrails, schema/policy validation, and robust fallbacks. Regularly supports rollout and adoption via developer workshops, integration guides, and customer calls, with strong production triage and observability practices.”
Mid-Level Full-Stack Engineer specializing in cloud platforms, cybersecurity web apps, and IoT
“Backend engineer with experience at Amazon building an API-driven service (APS) for large-scale prompt optimization jobs using AWS Step Functions, Batch/Fargate, DynamoDB, and S3, emphasizing idempotency, observability, and secure execution boundaries. Also led a multi-tenant enterprise policy/configuration backend refactor at MAMIT Cyber with versioned schemas, shadow writes, feature-flagged rollout, and PostgreSQL RLS-based tenant isolation.”
Mid-level Site Reliability Engineer specializing in cloud infrastructure, Kubernetes, and LLM applications
“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.”
Senior Software Engineer specializing in AWS data platforms and event-driven systems
“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.”
Executive IAM leader specializing in Zero Trust and identity security
“Hands-on technical founder building a new startup that is only weeks away from MVP and first design partner acquisition. Previously raised capital for an earlier venture, OverWatchID, and has again secured angel backing plus personal seed investment. Brings accelerator experience (SecureSet and Plug and Play), board-level VC exposure, and a strong track record across the full zero-to-one journey from product vision through early enterprise sales.”
Director of Engineering specializing in AI/ML platforms and cloud systems
“Senior engineering leader from IBM who has built and scaled enterprise AI/GenAI platforms across hybrid and multi-cloud environments, combining executive-level org leadership with hands-on debugging of production distributed systems. Particularly compelling for Director/VP roles needing someone who can unify architecture, platform strategy, and engineering execution across multiple teams.”
Mid-level Backend Software Engineer specializing in Java/Spring microservices and FinTech
“Backend engineer with Apple experience who owned production platform improvements end-to-end, including a Redis caching layer that cut API latency ~35–40% and reduced DB load. Has hands-on on-call/incident response and observability (CloudWatch), plus experience scaling Docker/Kubernetes microservices and operating Kafka-based telemetry pipelines with schema evolution, deduplication, and replay/backfill handling.”