Vetted AI Agents Professionals

“Designed and deployed end-to-end LLM-powered AI agent systems to automate knowledge-intensive workflows across marketing/GTM, recruiting, and support. Brings production reliability rigor (evaluation pipelines, monitoring, testing, A/B experiments) plus orchestration expertise (Airflow, Prefect, custom Python) and a track record of translating non-technical stakeholder goals into working AI solutions (e.g., personalized customer engagement agent at Lara Design).”

“ML/computer-vision practitioner who shipped a CycleGAN-based bilingual handwriting translation demo (English↔Telugu) for low-resource scripts using unpaired datasets, focusing on preserving handwriting style and real-time deployment via Gradio. Also delivered a medical imaging pipeline by fine-tuning ResNet-50 and ViT-B/16 for pneumonia detection, emphasizing reproducibility, measurable evaluation, and stakeholder-friendly iteration.”

Jai Vilatkar

Screened

Junior AI/ML Developer specializing in GenAI, LLM agents, and RAG systems

Pune, India2y exp

“Built and shipped an agentic RAG chatbot module for NexaCLM to answer questions across large volumes of contracts while minimizing hallucinations and incorrect legal interpretations. Implemented routing between vector retrieval and ReAct-style agent retrieval plus an automated grading/validation layer (cosine-similarity thresholds, retries) and deployed via GitHub Actions to Azure Container Apps, partnering closely with legal stakeholders to define risk/clause-focused objectives.”

“Full-stack product engineer who has built AI-assisted CRM and agent workflows in Project SARA and operational systems like payroll for a staffing platform. Stands out for combining React/TypeScript, Django/Postgres, real-time systems, and LLM orchestration with strong product instincts—delivering measurable gains in response time, conversion, and engineering leverage.”

“Currently acts as a tech lead for a team of AI agents building a mobile application, with agents handling requirements, design, development, testing, documentation, and JIRA/Confluence updates. Stands out for combining multi-agent orchestration with strong human-in-the-loop review and a clear interest in AI governance and authorization controls.”

“Full-stack and AI systems engineer who has built across ride-hailing, fintech, higher-ed support, and legal-tech workflows. Stands out for shipping production RAG/agent systems with careful grounding and human fallback, while also delivering hard backend architecture wins like geospatial dispatch scaling and cutting fintech payment latency from 60 seconds to 2 seconds.”

“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.”

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.”

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.”

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.”

Atharva Jagtap

Screened

Junior Full-Stack Software Engineer specializing in cloud and AI/ML applications

United States, Remote2y exp

“Full-stack engineer with hands-on experience across e-commerce personalization, enterprise RAG assistants, and cloud infrastructure automation. They’ve shipped AI features using Azure LLM APIs and vector search, improved recommendation engagement, and worked across frontend, backend, ML-informed analytics, and AWS infrastructure in early-stage environments.”

“Full-stack engineer with startup SaaS experience building workflow automation and case management platforms for business operations teams. Strongest in Python, TypeScript/React, and PostgreSQL, with hands-on ownership from backend architecture and APIs to production deployment on AWS; notably helped reduce manual processing and improve customer turnaround times in a high-ambiguity scaling environment.”

Eric Kerney

Screened

Senior Software Engineer specializing in geospatial and AI platforms

Kalamazoo, MI16y exp

“Full-stack product engineer with a strong geospatial/mapping focus who has built marketplace features, AI-enabled mapping MVPs, and Python API tooling in startup and client-services environments. Notable for combining React/Next.js front-end work with Python, spatial databases, and practical architecture/debugging decisions for enterprise-facing products used by customers such as Walmart and UPS.”

“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.”

Jonathan Lee

Screened

Director-level Engineering Leader specializing in agentic AI systems

Austin, TX19y exp

“Engineering leader and hands-on architect who built a team from scratch and owned everything from architecture and security to DevOps and deployment. Has led sophisticated AI/agentic systems in legal-tech and operations, including demand-letter automation, news/content generation, and human-in-the-loop fax routing, while also guiding major infrastructure and enterprise telephony transitions.”

Anuj Kumar

Screened

Senior Full-Stack Engineer specializing in GenAI and agentic AI

Abu Dhabi, UAE8y exp

“Backend-leaning full-stack engineer with startup experience owning core workflow automation services in a 10-15 person team. Built a scalable forms/workflow platform that cut process time from 30 days to 1 week, and has additional recent experience building agentic AI applications with FastAPI, Google ADK, and LiteLLM. Has worked on B2B SaaS products in solar digitization, construction/project management, and process automation.”

“Commercial and operations leader with 11 years building the revenue infrastructure behind enterprise growth, spanning Fortune 500 creative-tech engagements, a Series A SaaS launch, and an AI operations consulting practice. Particularly compelling for GTM and revenue roles: they have repeatedly built pricing, packaging, pipeline, and delivery systems from scratch, including scaling ARR 5x at a startup and deploying AI-driven outbound engines that materially increased pipeline efficiency.”

“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.”