Pre-screened and vetted.
Junior Software Engineer specializing in backend systems, FinTech, and applied AI
“Built and stabilized an AI-assisted document processing workflow for Possible Finance that supported underwriting without automating final loan decisions. Stands out for combining practical LLM integration skills with strong guardrails, validation, and fallback design in a financial workflow, delivering roughly a 35% reduction in document processing time.”
Executive engineering leader specializing in SaaS, cybersecurity, IAM, and telecom platforms
“Senior engineering leader with deep hands-on experience scaling and stabilizing complex SaaS platforms, including leading the OneLogin identity platform and managing globally distributed teams of up to 105 people. Particularly strong in reliability engineering, infrastructure modernization, and cross-functional execution, with a track record spanning platform unification, enterprise product delivery, and tailored Agile transformations.”
Junior Backend/Cloud Software Engineer specializing in serverless and distributed systems
“Backend-focused engineer who built a Python/Flask task-management API with JWT/RBAC, modular service/repository architecture, and PostgreSQL/SQLAlchemy performance optimizations (indexes, lazy loading, bulk ops, pooling). Also implemented multi-tenant data isolation strategies and built an OpenAI-powered document summarization workflow using chunking, async processing, Redis background workers, and caching to improve throughput.”
Mid-level Data Engineer specializing in real-time pipelines and cloud analytics
“Researcher from the University of South Dakota who built a production medical RAG system to help interpret model predictions by retrieving relevant clinical notes and medical literature, overcoming retrieval accuracy and imaging-dataset challenges through semantic chunking and metadata-driven indexing. Also has hands-on orchestration experience with Airflow and Azure Data Factory, plus a pragmatic approach to LLM evaluation and stakeholder-driven iteration.”
Mid-Level Full-Stack Software Developer specializing in Java/Spring, React, and AWS
“Full-stack engineer with end-to-end ownership experience, including building a real-time campaign/inventory dashboard at P&G using React/TypeScript, Spring Boot, GraphQL/REST, Redis, Docker, and AWS (EC2/RDS/S3) with Prometheus/Grafana observability. Demonstrates strong performance and reliability focus (p95 tuning, caching, idempotent event-driven ingestion with DLQs/reconciliation) and has shipped MVPs in ambiguous early-stage environments.”
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
“AI/ML engineer who has shipped production AI systems end-to-end, including an automated multi-channel (Gmail/WhatsApp/voice) candidate interviewing workflow and an enterprise RAG knowledge search platform. Demonstrates strong production rigor (monitoring, A/B tests, guardrails, schema validation, shadow testing) with quantified impact: ~60–70% reduction in interview evaluation time and ~20–30% relevance gains in RAG retrieval.”
Mid-level Full-Stack Developer specializing in FinTech and enterprise web platforms
“Financial-services AI engineer who shipped a production investment research assistant using RAG over internal research reports, SEC filings, and meeting transcripts, with a strong emphasis on truthfulness and guardrails. Built a structured evaluation loop (200+ golden test cases, RAG Triad metrics) that directly improved retrieval quality (e.g., fixing year-mismatch retrieval, boosting sensitive-query performance by 18% and cutting hallucinations to near zero) and scaled ingestion to ~10k messy documents with RabbitMQ + OpenTelemetry.”
Mid-level Software Development Engineer specializing in backend, data engineering, and ML systems
“ML/Backend engineer with ServiceNow experience building production-grade inference services on FastAPI with Docker/Kubernetes (autoscaling, health checks) and strong reliability practices (monitoring, retries/timeouts, fallbacks). Delivered measurable improvements including 30% lower API latency and 18% higher model accuracy, and built A/B testing plus drift-triggered retraining loops to keep models stable in production.”
Junior Full-Stack Software Engineer specializing in TypeScript, React, and Java microservices
“Software engineer with finance-domain experience who built an internal transaction management system end-to-end at Prospect Equities (TypeScript/React Native + Java Spring Boot microservices on AWS), delivering 40% lower query latency and 73% operational efficiency gains. Has also designed Terraform-provisioned, SQS-based distributed systems and scaled workloads to 10,000+ concurrent users, including monolith-to-SOA modernization that cut internal review time by 47%.”
Senior AI/ML Engineer specializing in Generative AI and LLM platforms
“Backend engineer focused on multi-tenant enterprise AI personalization and recommendation platforms, combining ML/LLM intent extraction with deterministic policy guardrails for compliance and auditability. Has hands-on AWS experience (ECS/Lambda/DynamoDB/S3) and led a careful DynamoDB single-table migration using dual write/read, canary + feature-flag rollouts, and strong observability/security (JWT/OAuth2, RBAC, Postgres RLS).”
Staff DevOps/SRE Engineer specializing in AWS, Kubernetes, and GitOps
“Infrastructure-focused engineer with Vonage experience modernizing early-stage cloud architecture (Terraform modularization, blue-green deployments, containerization, and zero-downtime database migration planning to Aurora). Also built a local end-to-end side project, Vastu AI, combining a custom-trained YOLO model (Roboflow-labeled data) with a locally hosted LLM via Ollama to generate a vastu compliance report from floor-plan images.”
Entry-Level Software Engineer specializing in data engineering and ML systems
“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”
Entry Software Engineer specializing in AI/ML and multimodal systems
“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”
Senior AI/ML Software Engineer specializing in Generative AI and RAG systems
“Built and owned Alight's AI-powered Search Summary feature end-to-end, using a RAG pipeline with OpenSearch and Bedrock, and drove a 20% increase in user feedback scores. Stands out for bringing rigorous production evaluation to LLM systems via live LLM-as-a-judge monitoring, and for experience with advanced agentic architectures, hybrid search, and reranking at scale.”
Director of Engineering specializing in SaaS platforms, AI-first product development, and telecom
“Technology leader with venture-backed company experience at LogicMonitor, where they aligned engineering strategy with business growth and long-term platform scalability. Demonstrates strong familiarity with the VC/studio/accelerator ecosystem and a thoughtful founder mindset centered on validating real problems, innovative solutions, and execution capacity.”
Mid-level Full-Stack Developer specializing in cloud-native FinTech applications
“Frontend engineer with HCL Tech experience building loan operations dashboards and React/TypeScript data-heavy interfaces. Stands out for combining maintainable component architecture with hands-on performance tuning, including a reported 30% load-time improvement in a production visualization-heavy application.”
Director-level Engineering Leader specializing in usage-based metering, FinOps, and GenAI platforms
“Founding Principal Engineer/Head of Engineering at Amberflo (Seed $5M Homebrew; Series A Norwest) who built and shipped an AI Gateway + real-time LLM cost metering/pricing MVP end-to-end (control plane/data plane, AWS infra, CI/CD). Known for extremely fast MVP cycles (often 1–2 weeks), scaling teams (50–60 hires), and driving major pivots (usage-based billing to FinOps) by repurposing an existing metering/pricing platform; based in Chicago and has led a Silicon Valley startup remotely with frequent Bay Area travel.”
Mid-level Software Engineer specializing in cloud platforms, SRE, and ML-powered engineering tools
“Platform-focused engineer/technical program leader working in silicon/wafer validation environments, with hands-on experience securing access to sensitive test results and engineering tooling. Has implemented RBAC/least-privilege controls with Azure Entra ID, Key Vault, PAM and integrated Checkmarx into dev workflows, while also deploying ML services on AKS using Bicep/Helm/Docker and Azure DevOps CI/CD with strong monitoring and incident response practices.”
Intern Robotics & Security Engineer specializing in autonomous systems and edge network security
“Robotics software engineer with UC Irvine capstone experience building an autonomous rover end-to-end: ROS 2 navigation (slam_toolbox + Nav2) on Jetson Xavier, depth point-cloud integration for obstacle avoidance, and an on-device speech-to-action interface that converts natural language into Nav2 goals. Also has prior full-time experience integrating a safety assurance decision engine into distributed autonomous drones over secured mesh networks, emphasizing reliable communication under real-world network constraints.”
Senior Full-Stack Engineer specializing in React/Node.js and enterprise web applications
“Senior frontend engineer with experience leading high-impact React/TypeScript products at HelloFresh and CAA, including an A/B-tested onboarding flow shipped across multiple international brands. Modernized a legacy .NET frontend to Next.js using SSR and performance techniques (caching/memoization/lazy loading) and implemented robust testing/monitoring (Cypress, Honeycomb, GA) in fast-paced, production-deploy environments.”
Intern-level Software Engineer specializing in AI/ML and time-series forecasting for finance
“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”
Senior Software Engineer specializing in Cloud DevOps and AWS automation
“Backend/automation engineer who led the design of an OOP Python test automation framework for AWS infrastructure (Behave + Jenkins), cutting regression effort from weeks to a 3–4 hour run. Has hands-on cloud and DevOps experience across AWS (boto3, ECS, AMI automation via GitHub Actions) plus data/migration work including on-prem-to-cloud Oracle Retail DB migration with rollback planning and a Kafka + ML fraud-detection streaming pipeline.”
Director-level Robotics Engineer specializing in robotic additive manufacturing and digital twins
“Head of Robotics at Orbital Composites who built the full ROS-based software stack ("OrbOS") for multi-robot KUKA-arm 3D printing of carbon-fiber composite geometries. Deep in motion planning and real-time control—created a pipeline to turn underconstrained toolpaths into optimal joint trajectories at massive command scale, plus redundant safety gatekeeping and a 250Hz synchronized robot+extruder controller. Has operated in a technical-founder capacity for ~6 years and values an engineering culture of openness, honesty, accountability, and high ownership.”
Senior Full-Stack Engineer specializing in AI/LLM and cloud-native SaaS
“Software engineer with strong end-to-end ownership across frontend, backend, data, and infrastructure, including real-time systems (Kafka/Postgres) and observability (Datadog). Built and productionized an AI-native RAG support assistant (OpenAI embeddings + Pinecone) with prompt/guardrail design, achieving 48% agent adoption and 30% faster responses. Experienced in legacy modernization and reliability work using feature flags, event/transaction replay, and rapid embedded delivery.”