Pre-screened and vetted.
Mid-level Full-Stack Developer specializing in cloud-native apps, AI/ML, and microservices
Senior Cloud DevOps Engineer specializing in Azure/AWS and hybrid cloud migrations
Executive Engineering Leader specializing in AI automation and cloud platforms
Mid-level Python Backend Developer specializing in FinTech and ML-driven fraud detection
Senior Full-Stack Software Engineer specializing in scalable microservices and cloud platforms
Mid-Level Full-Stack Python Engineer specializing in AI-powered web apps and cloud-native systems
Mid-level Full-Stack Python Developer specializing in cloud-native banking applications
“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”
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.”
Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment
“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).”
Mid-Level Java Developer specializing in FinTech microservices
“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.”
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.”
Senior Backend/Platform Engineer specializing in Python and AWS
“Backend/data engineer with hands-on production experience across Python/FastAPI services and AWS (Lambda, API Gateway, SQS, ECS) delivered via Terraform and GitHub Actions. Built Glue-to-Redshift ETL pipelines with Step Functions retry/catch patterns, schema evolution safeguards, and data quality checks; also modernized a legacy SAS monthly reporting system into Python microservices with rigorous side-by-side parity validation. Demonstrated strong SQL tuning skills with a reported improvement from 5 minutes to 15 seconds.”
Principal Enterprise Cloud Architect specializing in secure modernization and AI-ready infrastructure
“Bootstrapped founder building a cybersecurity framework for cloud-native applications and startups, differentiated by significantly faster end-to-end cloud environment delivery than traditional consulting. Has experience navigating pricing models (fixed price vs time & materials) using MVP and phased delivery, and has strong familiarity with the VC/accelerator landscape with interest in healthcare (details under NDA).”
Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps
“Full-stack engineer with experience at HubSpot, Accolite, and an early-stage USC alumni startup (Workup). Built and shipped end-to-end workflow automation features (dynamic input configuration with strict schema validation) driving ~25% faster configuration, and delivered an AI interview customization feature in a high-ambiguity startup setting that increased adoption by ~40%. Comfortable operating production systems on AWS with CloudWatch observability and CI/CD, and has built real-time web apps with caching/indexing for performance.”
Intern Software Engineer specializing in data engineering and AI agent systems
“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.”
Senior DevOps Engineer specializing in cloud infrastructure and CI/CD automation
“Infrastructure/operations engineer with hands-on IBM Power/AIX administration (LPAR/DLPAR, HMC, RMC) and PowerHA cluster failover experience, plus modern DevOps tooling across CI/CD, Kubernetes/Helm, and IaC (Terraform/CloudFormation/Ansible). Emphasizes controlled change management, drift prevention via Git-as-source-of-truth, and observability practices using Prometheus/Grafana.”
Executive CTO & AI Systems Architect specializing in cloud platforms and RAG products
“Technology leader with experience owning enterprise roadmaps and executing large-scale platform standardization during rapid M&A—most notably driving a tech roadmap across a 37-company portfolio at Regent, tackling technical debt and security gaps via unified cloud-native architecture, IAM/logging, CI/CD, and a global SRE model. Previously scaled an Adobe engineering org from 8 to 40+ across four regions, implementing clear org design, KPIs, and an extreme-ownership culture to support 24/7 operations and enterprise needs.”