Pre-screened and vetted.
Mid-Level Software Engineer specializing in data pipelines, APIs, and ML
“Software engineer whose recent work includes co-designing and building a "Shared Profile" feature for a social event-planning app (Again, Sometime). Previously at Pure Storage, set up Docker-standardized Ubuntu/Python environments to simulate hardware testbeds and support workload/performance regression testing for other engineering teams; no robotics/ROS experience.”
Mid-Level Backend Software Engineer specializing in payments, fraud systems, and AI agent infrastructure
“Early-career engineer who owned an end-to-end objective assessment/coding contest platform at an edtech startup, using Postgres + S3 and Redis (queues + ZSET) to decouple and scale code submission processing with worker sandboxes. Also implemented idempotency controls and set up monitoring and CI/CD while the rest of the team focused on curriculum.”
Mid-level Full-Stack Java Developer specializing in Healthcare and Financial Services AI
“Built and shipped production LLM/RAG systems at Mayo Clinic, including a conversational AI assistant for patient pre-consultation and a clinical-trial matching tool for doctors. Implemented HIPAA-compliant de-identification and guardrails, plus real-time feedback logging and fine-tuning that improved response accuracy by 15% and reduced admin workload by 25%.”
Mid-level DevOps Engineer specializing in cloud infrastructure, Kubernetes, and CI/CD automation
“Infrastructure/operations engineer with deep IBM Power/AIX experience (AIX 7.x, VIOS, HMC/vHMC) managing ~15–25 LPARs across production and DR, including live DLPAR changes and structured performance troubleshooting. Also hands-on with PowerHA/HACMP incident recovery and failover testing, plus broader DevOps delivery building Jenkins CI/CD for containerized microservices and Terraform/Ansible IaC across AWS and Azure, and leading Solaris SPARC to x86 migration cutovers.”
Mid-level Full-Stack Java Developer specializing in enterprise banking and healthcare systems
“Built and shipped a production LLM-powered customer support triage/resolution agent that automated ~60% of tickets, cutting response times from hours to seconds and improving first-response resolution by ~40%. Experienced designing multi-tenant, tenant-isolated agent architectures with RAG, schema-based tool calling/strict JSON validation, and strong reliability practices (guardrails, retries, fallbacks, monitoring), including safe integration with messy ERP-like data.”
Senior Data Engineer specializing in cloud data platforms and regulated analytics
“Data engineer at Capital One building AWS-based real-time and batch pipelines and backend data services for financial/fraud use cases. Has owned end-to-end pipelines processing millions of records/day, implemented dbt/Great Expectations quality gates, and tuned Redshift/Snowflake workloads (cutting query latency ~22–25% and reducing pipeline failures ~30–40%) while supporting 15+ downstream consumers.”
Mid-level Data Engineer specializing in cloud data platforms and big data pipelines
“Healthcare data engineer with hands-on ownership of claims/member data pipelines on a cloud analytics platform, spanning batch and streaming ingestion (Airflow/Kafka/Spark/Databricks) through serving for reporting. Emphasizes reliability and data quality via embedded validation, schema-drift detection, deduplication, and operational monitoring/incident response, plus pragmatic CI/CD and observability setup in early-stage/ambiguous projects.”
Junior Full-Stack Software Engineer specializing in AI and cloud-native systems
“Backend/systems-oriented engineer focused on building production-constrained LLM agent workflows that automate repetitive operator tasks via intent/entity extraction, retrieval grounding, and structured action recommendations with human-in-the-loop review. Emphasizes reliability through deterministic orchestration, strict tool/function schemas, observability, and disciplined evaluation/feedback loops, with strong experience handling messy multi-service operational data and idempotent execution.”
Senior Backend Engineer specializing in real-time data platforms for FinTech and Healthcare
“Backend/data engineer with experience at JPMorgan building near real-time payment risk and fraud scoring pipelines using Python, Spark Structured Streaming, and Delta Lake, emphasizing auditability, security, and data correctness (dedupe/late events) to reduce false positives. Also led a legacy-to-cloud migration of claims/eligibility data at Cogna with parallel runs, phased rollout, and healthcare-specific validation (ICD-CPT mapping).”
Mid-level Robotics & AI Researcher specializing in human-robot interaction and reinforcement learning
“Robotics software engineer who built an end-to-end mobile manipulation platform (Franka Panda on a Clearpath Ridgeback) for a simulated-kitchen human-robot interaction study with natural speech commands, implemented in Python/ROS. Has hands-on experience integrating diverse sensors (RealSense, LiDAR, biosignals) with deep learning frameworks (PyTorch, Hugging Face) and fine-tuning GPT-Neo, plus simulation (Gazebo) and modern deployment practices (Docker/Kubernetes, CI/CD).”
Junior Quantitative Analyst and Full-Stack Engineer specializing in FinTech and web platforms
“Backend/distributed-systems engineer with AI infrastructure experience who built an AI-driven video generation platform, focusing on an asynchronous FastAPI-based orchestration layer between user APIs and heavy inference services. Strong in production instrumentation and latency/concurrency optimization; actively learning ROS 2 but has not yet worked on physical robotics or ROS-based deployments.”
Senior Engineering Manager specializing in platform, data/ML, and identity/access systems
“Senior engineering leader from Goodyear’s AndGo startup-like division who scaled the org from 12 to 30+ across pod-based teams and introduced an Architect Guild/ARD governance model. Led a 4-month Europe launch requiring AWS regional infrastructure, GDPR compliance, i18n/l10n, and new EMEA reporting pipelines, and has hands-on depth in API performance, incident response, and GraphQL/Hasura adoption to boost product velocity.”
Senior Full-Stack Software Engineer specializing in Python, FastAPI/Django, and Azure
“Backend/data engineer with production experience building real-time IoT telemetry pipelines for wind/solar assets at Siemens (FastAPI on Azure Event Hubs/Service Bus, Cosmos DB + SQL Server) and deploying GPS/fleet telematics microservices on AWS ECS Fargate with Terraform and blue/green CI/CD. Demonstrated strong reliability and performance chops, including a 30s-to-<100ms SQL optimization and owning a Kafka pipeline incident resolved in ~20 minutes.”
Senior Frontend Engineer specializing in React/Next.js for enterprise FinTech and AI platforms
“Full-stack engineer with strong real-time and applied AI experience: built an internal AI “virtual subject matter expert” platform at Shell Energy serving ~1,800 employees with sub-200ms response streaming. Diagnosed AWS load balancer WebSocket disconnects and shipped reliability fixes (heartbeats, reconnect/backoff, session resume), and implemented AI production guardrails (eval suite, drift monitoring, confidence thresholds, citations, human-in-the-loop) that reportedly cut hallucinations by ~90%.”
Senior Platform/DevOps Engineer specializing in CI/CD and Observability
“DevOps engineer focused on CI/CD who built and productionized LLM/MCP-based chat agents integrated into Cisco Webex to help developers troubleshoot PRs and pipelines via GitHub/Jenkins data. Strong in operationalizing agentic systems with observability (OpenTelemetry/Grafana), user-scoped rate limiting, and Kubernetes-based scaling, and has presented demos on agent SDK capabilities and DORA metrics dashboards.”
Mid-Level Full-Stack Software Engineer specializing in enterprise AI, data pipelines, and scalable APIs
“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”
Senior .NET Full-Stack Developer specializing in cloud-native enterprise apps
“Full-stack TypeScript engineer who built and operated a production order/inventory platform (React + NestJS/Node + PostgreSQL) with Redis and RabbitMQ for performance and background workflows. Emphasizes correctness in production via idempotency, retries/backoff, DLQs, and observability, and has also delivered external-facing REST APIs (Swagger, versioning, JWT/RBAC) plus resilient checkout browser automations using Playwright/Puppeteer.”
Mid-level Software Engineer specializing in backend systems, cloud-native apps, and AI platforms
“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”
Junior Full-Stack Software Engineer specializing in scalable, AI-powered web apps
“Frontend-leaning engineer with production React experience and hands-on Next.js App Router patterns (Server/Client Components, Route Handlers, caching/revalidate decisions). Has built internal sales dashboards and optimized both React UI performance and SQL Server-backed analytics queries, and previously created an onboarding framework at Adobe that evolved into a configurable, multi-team reusable platform in a lean environment.”
Mid-level Software Engineer specializing in cloud data platforms and LLM applications
“LLM/agent builder with experience shipping production LLM features at an early-stage ed-tech mental wellness startup (conversation analysis + structured feedback via FastAPI, OpenAI API, Render, CI/CD). Also built a multi-step dining concierge agent using OpenSearch over Yelp data with fallback query relaxation, and has enterprise data engineering experience at Capgemini migrating databases to Snowflake with robust ETL normalization and data-quality handling.”
Mid-level Data Engineer specializing in lakehouse ETL and analytics engineering
“Data engineer with strong end-to-end ownership of production lakehouse pipelines (Snowflake + Databricks + Airflow + dbt + Great Expectations), handling 8M+ records/month and 500K+ daily CDC updates. Delivered measurable reliability and efficiency gains (41% cost reduction, freshness improved from 4h to 30m, 35% fewer downstream incidents) and has experience building a lakehouse platform from scratch across 12 source systems.”
Executive CTO specializing in digital health platforms, cloud & AI, and FHIR/HL7 interoperability
“Healthcare diagnostics/health tech founder building Casandra.ai, an API-driven lab test catalog and ordering platform designed to standardize fragmented test catalogs and integrate into provider workflows via FHIR. Bootstrapped and built a deploy-ready product, drawing on prior startup experience and accelerator participation (Health Box, DreamIt Ventures).”
Executive IT & PMO leader specializing in digital commerce and enterprise transformation
“IT leader with hands-on M&A integration experience (including day-one readiness) across notable brands (e.g., Billabong, Marucci Sports) and product-focused organizations (Oakley). Brings broad IT domain expertise (AI, business systems, digital sales technologies) and has worked with multiple startups; interested in joining an existing startup to help it scale rather than founding a new company.”
Mid-level Software Engineer specializing in backend microservices and real-time streaming
“Built and owned an end-to-end LLM-powered enterprise retrieval pipeline at ServiceNow, spanning ingestion of structured/semi-structured sources through vector retrieval and real-time API serving. Focused heavily on reliability and quality (multi-stage validation, monitoring, evaluation pipelines) while also driving performance improvements (~35% faster responses) via caching, async processing, and SQL/query optimization.”