Pre-screened and vetted.
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Senior Software Engineer specializing in cloud platforms, data pipelines, and ML
Mid-Level Software Engineer specializing in Ads Serving and Machine Learning Systems
Executive Software Engineering Leader specializing in AI/ML, cloud platforms, and distributed systems
Senior Software Engineer specializing in AI/ML, search, and scalable cloud platforms
Mid AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Director-level engineering leader specializing in AI platforms and consumer applications
Mid-level Software Engineer specializing in FinTech backend systems
Mid-level Full-Stack Software Engineer specializing in scalable FinTech and analytics platforms
“Senior full-stack engineer with 5 years of experience across Bank of America, AT&T, and NextAI/XAI, building cloud-native, high-availability products spanning React, Node, Java, Kotlin, Python, and AWS. Particularly compelling for teams needing someone who can own architecture, implementation, DevOps, and UX polish end-to-end—from a real-time loan eligibility platform handling 50,000+ daily requests to live event dashboards that improved operations and helped drive $250K in ARR.”
Senior Backend Engineer specializing in Node.js, Java, and regulated SaaS platforms
“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%.”
Senior Backend Engineer specializing in distributed systems and cloud microservices
“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.”
Director-level Software Development Manager specializing in cloud DDoS protection
“AWS Software Development Manager leading globally deployed, production-critical DDoS protection (L3/L4) across AWS. Known for scaling teams and driving cross-org tiger-team initiatives from concept through worldwide rollout, including performance-focused Python architecture changes and a major JDK 8→21 migration while maintaining strict backward compatibility. Also led an internal SDK-like integration framework improving APIs, documentation, and onboarding for major AWS service teams.”
Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization
“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”
Engineering Director specializing in backend & data platforms for enterprise SaaS and cybersecurity
“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.”
Director-level Engineering Leader specializing in data platforms, cloud systems, and LLM products
“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.”
Director-level product and engineering leader specializing in AdTech, FinTech, and platform systems
“Former tech professional and repeat founder who previously built Promote.co, pitched a marketplace-focused ad platform to Expa Ventures, and raised capital to build the product. Has spent the last two years independently developing and using stock market strategies, and is now looking to return to tech to solve meaningful, difficult problems.”
Mid Software Engineer specializing in distributed backend systems
“Engineering candidate deeply embedded in AI-native development, currently using tools like Cursor and Claude Code to generate most of their code and building internal agents for on-call monitoring, anomaly detection, and automated incident mitigation. Particularly interesting for teams exploring AI-first engineering workflows, multi-agent development setups, and operational automation at scale.”
Principal Software Engineer / Tech Lead specializing in distributed systems, payments, and reliability
“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.”
Mid-Level Software Engineer specializing in cloud-native backend systems and FinTech
Staff Software Engineer specializing in agentic AI and distributed systems
Engineering Manager / Software Development Manager specializing in backend platforms and ML forecasting
Executive Engineering Leader specializing in AI, Cloud Platforms, and Personalization at scale