Pre-screened and vetted.
Junior Full-Stack Software Engineer specializing in ML, cloud infrastructure, and mobile apps
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and agentic RAG systems
Senior GenAI Engineer specializing in production LLM systems and agentic AI
Mid-level Data Scientist specializing in GenAI, LLM orchestration, and MLOps
Senior Software Engineer specializing in AI agents, RAG, and enterprise search in Financial Services
Mid-level Product Manager specializing in AI-driven product strategy and analytics
Senior QA Automation Engineer specializing in API/UI automation and CI/CD
Director-level Executive Operations & Administrative Leader in government, nonprofit, and private office settings
“Executive operations/project leader who managed cross-entity priority initiatives for Eric Schmidt’s family office, driving alignment through structured reporting and dashboards. Led a board-level digital transformation at ACC, moving a 14-member Board of Trustees from paper processes to board software, and brings high-discretion experience supporting Senator Warner.”
Mid-Level Software Engineer specializing in geospatial AI and cloud security automation
“Cloud engineer and cloud OS SME (Chevron) who productionized large-scale security remediation—using Tanium and Ansible to address CIS benchmark noncompliance across 5,000+ servers with robust logging and RCA handoffs. Also drives adoption of a geospatial AI refinery inspection product by consolidating siloed imagery into an enterprise geospatial database, and presents internally on agentic/LLM tooling (LangChain/LangGraph, LangSmith observability).”
Executive AI Product & Controls Engineering Leader specializing in agentic video editing and EV systems
“Startup builder (MagicSeven) who designed and implemented a browser-based, agentic video editor end-to-end, including an AWS event-driven multimodal LLM “indexing” pipeline and an orchestration LLM agent for searching and manipulating footage. Demonstrates deep video file/codec knowledge plus practical production hardening of LLM workflows (format validation, plan/execute, S3-based state for debuggability).”
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Mid-level AI/ML Engineer specializing in LLMs, NLP, and analytics automation
“AI/ML Engineer (TCS) who built and deployed a production LLM-powered audit transaction validation service to reduce manual review of unstructured transaction records and comments. Implemented a LangChain/Python pipeline for extraction/normalization and discrepancy detection, with strong production reliability practices (decision logging, dashboards, labeled eval sets) and a human-in-the-loop auditor feedback loop to improve precision/recall under strict data-sensitivity and near-real-time constraints.”
Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS
“Engineering leader (Director/VP level) who has repeatedly aligned product and engineering through ROI-driven quarterly roadmaps and strong stakeholder communication, including board presentations. Built a parallel cloud team to migrate an on-prem product to the cloud, credited with delivering $9M ARR, and led a Python monolith-to-serverless event-driven microservices transformation. Currently manages distributed teams across Mexico, India, and the US using pod-based structures, clear KPIs, and a supportive accountability culture.”
Senior/Lead Game Developer specializing in Unity and cross-platform multiplayer games
“Veteran Unity game developer with extensive multiplayer networking experience (Photon PUN2/Quantum/Fusion, Unity Netcode), including work on Payday: Crime War and an in-development arena battler using Invector + PUN2. Also builds cloud backends for Unity titles (Azure/PlayFab/Firebase, SQL, CI/CD) and actively uses multiple AI assistants to speed up architecture and implementation.”
Intern LLM/GenAI Engineer specializing in RAG, agentic systems, and low-latency inference
“Interned at Larsen & Toubro where they built and deployed an agentic RAG document question-answering system to reduce time spent searching documents and improve trustworthiness. Implemented ReAct-style multi-step orchestration with LangChain/LlamaIndex plus evidence-bounded generation, grounding/citations, and rigorous evaluation—cutting latency ~40%, hallucinations ~35%, and unsafe outputs ~40% while collaborating closely with non-technical business/ops stakeholders.”
Mid-level AI Solutions Engineer specializing in enterprise GenAI and automation
“Built and shipped multiple production LLM/agentic systems, including an agentic RAG NL-to-SQL analytics app that cut manual reporting from 9 hours/week to 15 minutes by grounding on schema-aware retrieval and robust fallback/monitoring. Also implemented a LangChain supervisor-orchestrated enterprise IT automation agent that routes requests for search, identity validation, and action execution, and created a RAG search tool spanning Jira/Confluence/SharePoint for operations stakeholders.”
Junior Applied AI Engineer specializing in LLMs, RAG, and agentic systems
“Co-founded a healthcare AI startup building and deploying software directly with end users, emphasizing rapid shipping, deep user interviews, and workflow-first adoption. Has hands-on production deployment experience on AWS (including diagnosing a silent AWS App Runner failure caused by an ARM vs amd64 Docker build mismatch) and is motivated by customer-facing, travel-heavy roles to keep engineering tightly connected to real-world usage.”
Senior AI/ML Engineer specializing in Generative AI and RAG
“ML/NLP practitioner at Morf Health focused on unifying fragmented healthcare data by linking structured patient/encounter records with unstructured clinical notes. Has hands-on experience with transformer embeddings, vector databases, and domain fine-tuning, plus rigorous evaluation (precision/recall) and human-in-the-loop validation with clinical SMEs to make pipelines production-grade.”
Mid-level Generative AI Engineer specializing in LLM systems and RAG
“Currently at Huntington Bank, built a production-grade RAG system that helps business/operations teams get grounded answers from large volumes of internal enterprise documents. Owns ingestion and FastAPI backend, tuned hybrid BM25+vector retrieval and chunking for relevance, and evaluates reliability with metrics and observability (LangSmith, CloudWatch, Prometheus/Grafana) while partnering closely with non-technical stakeholders.”