Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Senior Data Scientist and Machine Learning Researcher specializing in NLP, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in Generative AI and RAG assistants
Mid-level DevOps Engineer specializing in Azure cloud infrastructure and CI/CD
Mid-level Full-Stack Software Developer specializing in cloud microservices and healthcare interoperability
Junior Data Engineer specializing in cloud ETL/ELT and lakehouse platforms
Senior Full-Stack Software Engineer specializing in Python, React, and LLM-powered applications
Mid-level Generative AI & ML Engineer specializing in production LLM and RAG systems
“AI/ML engineer who shipped a production blood-test report understanding and personalized supplement recommendation product, using a LangGraph multi-agent pipeline on AWS serverless with OCR via Bedrock and RAG over vetted clinical research. Also built end-to-end recommender system pipelines at ASANTe using Airflow (ingestion, embeddings/features, training, registry, batch scoring/monitoring) with KPI reporting to Tableau, with a strong focus on safety, evaluation, and measurable reliability.”
Junior AI Software Engineer specializing in LLM agents, RAG, and healthcare NLP
“Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.”
Mid-level Full-Stack Engineer specializing in cloud-native, event-driven data platforms
“Backend/data engineer with hands-on production experience building Python (FastAPI/Flask) data enrichment services secured with Okta OAuth2 and monitored via Splunk/Dynatrace. Has delivered AWS event-driven and data-migration solutions (Lambda + Kafka to EKS; Glue from on-prem Oracle to S3/data lake) and modernized Informatica match/merge logic to cloud services using parallel-run parity validation and stakeholder sign-off.”
Junior Full-Stack Software Engineer specializing in Java/Spring Boot and React
“Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).”
Mid-level SRE/DevOps Engineer specializing in cloud infrastructure automation and Kubernetes
“Cloud/SRE-style engineer at TDS supporting revenue-critical transportation SaaS platforms on AWS/GCP with Kubernetes. Has hands-on experience leading high-impact production work including DDoS mitigation, zero-downtime MSSQL→PostgreSQL migration using CDC, and building secure GitHub Actions + ArgoCD delivery pipelines and Terraform-based GKE infrastructure.”
Chief Architect specializing in microservices, cloud infrastructure, and enterprise AI agents
“Startup-focused engineering leader applying for a CTO role; previously served as founding CTO of a tech startup and held engineering/architecture roles across several others. Evaluates new ventures through market research and market demand, and emphasizes building from the ground up with strong teams (has not personally participated in fundraising).”
Senior Cloud DevOps Engineer specializing in AWS architecture, IaC, and DevSecOps
“DevSecOps/AWS infrastructure engineer at Madison Logic who owns a 15-account AWS footprint and treats nearly all AWS resources as code (Terraform/CloudFormation). Led a CI/CD platform migration (Bitbucket → GitLab + GitHub Actions) supporting WordPress and containerized microservices, improving release frequency to weekly/daily, and has hands-on production incident response experience on ECS Fargate using Datadog with fast rollback via immutable ECR tags and task definition revisions.”
Intern AI Engineer specializing in LLMs, NLP, and conversational search
“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”