Vetted AI Agents Professionals

“Software engineer with end-to-end ownership of a Qt/C++/QML desktop app for monitoring/configuring equipment, including hands-on UI performance optimization. Also built a web-based AI agent interface (React/TypeScript + Python Flask) with strong API contract discipline and async state handling, and improved microservices reliability using idempotency, DLQs, and observability. Created an internal CI/CD automation tool adopted across engineering and operations teams, adding safer rollbacks and better error messaging based on feedback.”

“Built a production lead-generation system using AI agents that researches the internet for relevant leads and integrates RAG-based contact enrichment/shortlisting aligned to existing CRM data, enabling sales reps to focus more on selling. Also has hands-on AWS data orchestration experience (Glue, Step Functions) moving raw data into Redshift and evaluates agent performance with human-in-the-loop plus BLEU/perplexity metrics.”

“Co-founder at Skarbe who built “Oskar,” an autonomous sales agent that handles inbound email, lead qualification, and automated follow-ups using a multi-agent architecture (OpenAI Agents SDK) with a human-in-the-loop learning phase for reliability. Also owned scaling and reliability of Gmail/Outlook sync, including a Node.js-to-Rails migration and incident response during a Product Hunt launch that generated hundreds of signups and a ~2M-email queue.”

Mark Eagle

Screened

Executive Technology & Operations Leader (CTO/COO) specializing in scaling SaaS and enterprise software

Denver, Colorado29y exp

“Operations leader and advisor (former COO at College Partnership; also worked with Founders Advisors) who rebuilds and scales early-stage operations using Lean Startup experimentation and KPI-driven execution. Notably centralized a call-center function, implemented scripts/SLAs/metrics, and iterated staffing based on conversion and response-time data while mentoring non-ops founders on MVPs, SMART goals, and tactical operating plans.”

Vikram Sandigaru

Screened

Mid-level AI Engineer specializing in AI agents, RAG pipelines, and LLM evaluation

Boston, US3y exp

“Built and shipped production LLM systems at Founderbay, including a low-latency voice agent and a graph-based multi-agent research assistant. Strong focus on reliability in real workflows—hybrid SERP + full-site scraping RAG, grounding guardrails, validation checkpoints, and transcript-driven evaluation—plus performance tuning with async FastAPI, Redis caching, and containerization. Also partnered with a non-technical ops lead to automate post-call follow-ups via call summarization, field extraction, and tool-triggered actions.”

Keeravani Chekuri

Screened

Mid-level AI/ML Engineer specializing in LLM systems and MLOps

Boston, MA3y exp

“Built and deployed an AI tutoring assistant end-to-end at Nexora School, spanning discovery with school districts, multi-agent LangGraph/RAG architecture, AWS Bedrock migration, and post-launch stabilization. Stands out for combining hands-on LLM systems engineering with strong educator-facing trust building, FERPA-driven architecture decisions, and disciplined production practices around evals, logging, and messy document ingestion.”

“Robotics/AV-focused candidate who contributed to an F1TENTH autonomous vehicle college project, building key autonomy components from raw sensor data to driving commands. Strong in perception and state estimation (visual odometry, particle-filter localization), plus mapping (occupancy grids) and planning/control (RRT, Gap Follow, PID), with hands-on ROS tooling and simulation validation in Gazebo/RViz and ROS environment containerization using Docker.”

“Graduate-level candidate who uses AI as a disciplined engineering assistant rather than an autonomous replacement, with hands-on experience coordinating manual multi-agent coding workflows across planning, implementation, and testing. They emphasize scoped execution, clear constraints, and human ownership of final merges, suggesting a thoughtful and practical approach to AI-augmented software development.”

“Head of Engineering and former long-time development agency owner (~10 years) pursuing CTO roles, with a strong 0-to-1 mindset focused on PMF/TAM and rapid MVP delivery. Led a 3-person team to design and ship a simplified website builder in one month (2023) that is now growing 10–15% YoY, and advocates for agentic AI/spec-driven development (BMAD principles, Claude Code) to help small teams move faster than traditional larger orgs.”