Pre-screened and vetted.
Junior Software Engineer specializing in full-stack web and Android development
Junior Software Engineer specializing in backend microservices and network observability
Senior Applied AI Engineer specializing in LLM systems and full-stack product development
Junior Software Engineer specializing in full-stack development and computer vision
Senior AI/ML Engineer specializing in Generative AI and Computer Vision
Mid-level Full-Stack Software Engineer specializing in FinTech
Entry-level Software Engineer specializing in systems and healthcare data
Senior Full-Stack Engineer specializing in web, mobile, and product growth
Director-level AI/ML engineering leader specializing in platform and product development
Executive AI Architect specializing in enterprise cloud and FinTech solutions
“Candidate brings an operator-to-founder profile with leadership experience in IT and Business Systems and a strong grasp of how ideas become venture-backable products. They speak fluently about startup evaluation criteria such as TAM, technical defensibility, speed to scale, and AI differentiation, and appear especially motivated by building solutions end-to-end in startup or venture studio environments.”
Senior Frontend Developer specializing in scalable web applications
“Frontend engineer with experience at Target, Fortinet, and Groupon, focused on complex browser UI modernization and performance. Notable work includes rebuilding Target's internal uploader to support nearly 1GB uploads with granular progress/retry UX, and helping Fortinet incrementally migrate a large Jinja-based application to Vue to improve responsiveness and reduce backend load.”
Junior Software Engineer specializing in full-stack, cloud serverless, and AI systems
“SDE who worked on an MGICS Lab robotics project building a multi-agent model to help agents understand tasks and generate robot instructions, emphasizing task-splitting, checking, and a reflection agent to improve accuracy. Also has experience using GitHub with automated CI/CD pipelines.”
Senior Software Engineer specializing in document workflows and API platforms
“Backend engineer with experience building queue-driven Python/Flask systems using Celery, Redis/RabbitMQ, and SQLAlchemy/Postgres, including async/non-blocking architectures for concurrency. Also built a patient-facing full-stack app integrating LLMs (OpenAI/Claude) with streaming responses for real-time UX, and previously delivered high-throughput, reliability-critical background workflows at Dropbox (document expiration with batching, retries, and cache/side-effect handling).”
Mid-level Backend Software Engineer specializing in AWS cloud and FinTech platforms
“JP Morgan engineer and Texas A&M student web developer who has owned production systems end-to-end, including a real-time ML training workflow that improved internal search relevance by 30%. Experienced with AWS cloud migrations and operating containerized services on ECS with CloudWatch+ELK observability, Terraform infra, and Spinnaker CI/CD; also built event-driven pipelines with RabbitMQ and Elasticsearch at 1M+ record scale.”
Mid-level Data Engineer specializing in cloud data pipelines and enterprise data platforms
“Data engineer/backend engineer who owns large-scale, real-time event pipelines on AWS end-to-end, including a petabyte-scale CDC ingestion flow from multiple Postgres DBs into Redshift. Re-architected a legacy DynamoDB+S3 approach into a Delta Lake + DuckDB/PyArrow-compatible design, improving performance dramatically (e.g., ~600s to ~10s for 1k records) and increasing reliability at high file volumes.”
Intern Software Developer and ML Researcher specializing in medical imaging and computer vision
“AI/ML practitioner with experience spanning audio/LLM applications (built "Iota" using Whisper, tiktoken, and a local Ollama-served LLM) and healthcare ML (Facemed.ai; UChicago Radiology). Demonstrates a production-oriented mindset—focus on data/model fit, deterministic field testing, and operational safeguards—and has improved research evaluation workflows via a hash-table-based concurrent model tracking approach.”
Junior AI/ML Systems Engineer specializing in LLM infrastructure and distributed training
“Built and shipped a production NMT system translating medical documentation for a rare/low-resource language, tackling data scarcity with retrieval-driven pattern matching plus dictionary/grammar- and LLM-based augmentation and validating quality with a linguistic expert. Also develops agentic LLM workflows with LangChain/LangGraph (including a deep-research style system) and has experience aligning medical AI deployments with clinician-defined risk metrics and human-in-the-loop decision making.”
Junior Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”
Junior Full-Stack Software Developer specializing in web platforms and AI workflows
“Software engineer who built and shipped “Counsellor AI,” a production LLM-powered academic advising agent for college students using AWS Bedrock and grounded RAG over official university catalogs/policies. Emphasizes reliability through structured JSON outputs, multi-step orchestration with shared state, and strict intake/validation gates to prevent hallucinations and invalid academic plans; also has experience hardening messy telecom operational data pipelines with normalization, permissions, fallbacks, and idempotent patterns.”
Executive Applications Development & Analytics Leader specializing in enterprise transformation
“Candidate has prior startup experience building systems and has firsthand experience with a venture that lost angel funding. They show thoughtful reflection on why the startup failed—emphasizing unclear success criteria, weak funding planning, and lack of team consensus—and would seek experienced advisors earlier in future ventures.”
Director-level technology executive specializing in enterprise software and architecture
“Candidate is not currently pursuing a startup and has no familiarity with the VC/accelerator ecosystem, but shows a thoughtful founder mindset centered on building from scratch, evaluating user impact and implementation feasibility, and avoiding financially reckless entrepreneurship.”