Vetted Generative AI Professionals

Pavan Kumar Malasani

Screened

Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and GenAI

Remote, USA4y exp

“GenAI/ML engineer in Citigroup’s finance environment who has deployed production RAG systems for investment banking under strict privacy and model-risk constraints. Built an internal-VPC Llama2 + Pinecone + LangChain solution with NER redaction and citation-based verification to prevent hallucinations, delivering major time savings, and also partnered with global finance executives to ship an AI early-warning indicator for treasury/liquidity risk.”

Yukti Kamthan

Screened

Senior Software Engineer specializing in AI/ML and data systems

Mumbai, India10y exp

“Built and shipped production LLM/AI agent systems including an NL-to-SQL query agent with semantic search and Redis-based caching, using schema-aware prompting and threshold validation to reduce hallucinations. Has orchestration experience running ML microservices on Kubernetes and automating event-driven insurance (P&C) workflows (claims/policy + fraud checks), reporting ~60% manual overhead reduction and ~99% uptime, with strong monitoring/drift-detection and business-facing Power BI reporting.”

Abhay Ravi Kumar

Screened

Junior Software Engineer specializing in backend, cloud DevOps, and ML/NLP

Bengaluru, India1y exp

“DevOps/data-automation professional with HPE experience who has deployed containerized microservices to AWS EKS and built an end-to-end observability stack (Prometheus/Grafana/CloudWatch via Terraform), reporting zero-downtime deployments and ~40% faster incident response. Also extends Python ETL automation for procurement/operations teams (rules engine, validation, performance tuning) and bridges SAP ERP data into Power BI/Qlik dashboards through close on-site user collaboration.”

Pandari G

Screened

Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems

San Francisco, USA5y exp

“GenAI/LLM engineer with production deployments in both fintech and retail: built an AI-powered mortgage document analysis/automated underwriting pipeline at Fannie Mae (OCR + custom LLM) cutting underwriting review from 3–4 hours to under an hour with privacy-by-design controls. Also helped build Sephora’s GenAI product advisory bot using LangChain-orchestrated RAG (Azure GPT-4, Azure AI Search, MySQL HeatWave vector search), focusing on grounding, evaluation, and compliance-aware architecture choices.”

“Recruiter with GE Healthcare experience who successfully led a full-desk search for a Regional Sales Director in a newly acquired business unit. Stands out for navigating ambiguous, change-heavy hiring environments with targeted sourcing, transparent candidate messaging, and data-driven hiring manager alignment.”

“Candidate founded a non-profit and developed unconventional funding mechanisms for it, including a book whose proceeds support the organization and a patented AI stack designed for licensing royalties. They also bring early startup experience and acquisition due-diligence exposure, and are specifically interested in contributing their technical and venture incubation background within an existing entrepreneurial company rather than founding a new one.”

Kishore Koduri

Screened

Director-level Enterprise Architecture leader specializing in AI and platform transformation

Akron, OH29y exp

“Entrepreneurial candidate with deep technology expertise who has already acted as a founder/principal across a real estate venture and early-stage tech startups. Most notably, they raised approximately $1-2M for a real estate project and describe hands-on ownership from ideation and business case development through ROI validation and investor commitment.”

Vamsi Reddy

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial ML systems

Nashville, TN5y exp

“ML/AI engineer with hands-on experience shipping both predictive healthcare models and clinical GenAI assistants into production. They combine strong MLOps depth across Azure and AWS with healthcare-specific safety thinking, including PHI guardrails, retrieval grounding, and production monitoring, and they also built internal Python tooling for fraud ML workflows at Capital One.”

“AI/ML engineer with production experience across both classical ML and Generative AI, including a real-time banking fraud detection platform at Deloitte and a RAG-based cybersecurity threat analysis feature at Accenture. Stands out for owning systems end-to-end—from feature pipelines and model tuning through deployment, monitoring, retraining, and API/platform reliability—with measurable impact on fraud accuracy, false positives, and SOC analyst efficiency.”

Saumya Pailwan

Screened

Junior Software Engineer specializing in applied AI and audio ML

Evanston, IL2y exp

“Engineer with unusually mature experience leading AI-assisted development, including orchestrating multiple coding agents across a data pipeline feature as if managing a small engineering team. Stands out for balancing aggressive adoption of AI tools with disciplined judgment around architecture, security, and merge quality, and for translating that experience into stronger tech leadership.”

“Built and shipped a production LLM feature that converts natural-language search requests into Lucene queries for OpenSearch-backed device event data, improving usability for non-technical users. Brings hands-on experience across the full stack of agentic systems: model training, FastAPI/React integration, Kubernetes deployment on AWS, event-driven orchestration with NATS/Kafka, and production-grade evaluation/observability.”

“AI engineer and current tech lead building a RAG-based multi-agent QA platform for financial document analysis at significant scale (40,000-50,000 documents). They combine Python, CrewAI, FastAPI, Hugging Face embeddings, Pinecone, and AWS SageMaker to deliver retrieval, calculation, summarization, forecasting, and visualization workflows, while leading a small cross-functional team.”

Arpan Acharya

Screened

Executive engineering leader specializing in AI, data platforms, and healthcare SaaS

Pittsburgh, PA21y exp

“Senior product and platform engineering leader with experience spanning startup-style incubation and large-scale enterprise transformation at Omnicell. Led architecture used by 400+ engineers, scaled a new data-focused team from 10 to 60, and drove an inventory optimization platform that helped secure the company’s first $100M+ multi-product contract.”

“Frontend engineer with Oracle Cerner experience building healthcare operations UIs where accuracy, compliance, and workflow efficiency matter. They’ve owned a sophisticated React-based patient record validation and merge interface and also show solid performance instincts through render optimization, state management, and TypeScript-based API modeling.”

Abhinita Sanabada

Screened

Senior Software Engineer specializing in AI/ML systems and FinTech platforms

San Jose, CA9y exp

“Master’s student in Data Science at San Jose State University with prior software engineering experience at JPMorgan Chase and Zap Labs. She combines enterprise backend reliability work in financial systems with hands-on full-stack AI workflow projects, including a recruiting automation system built with React/Next.js, FastAPI/Node, Kafka, and WebSockets, with a strong emphasis on observability, human-in-the-loop controls, and maintainability.”

“Front-end/full-stack engineer with hands-on ownership of a sophisticated healthcare digital ID card platform at Centene, spanning React/Next.js UI and Spring Boot BFF architecture. Stands out for combining browser-level debugging, reusable component design, and secure multi-system integration to improve mobile usability, reduce production issues, and support adoption of digital member ID cards.”

“Full-stack product builder with strong GTM and applied AI experience, including end-to-end ownership of a production lead intelligence platform that combined React/TypeScript, Python services, external data enrichment, and LLM orchestration. Notably reduced SDR research time from 15-20 minutes to under 2 minutes per account and also drove an 8% revenue increase at Finding Pi by building a customer segmentation framework from analysis of 45k+ users.”

“Frontend-focused engineer with experience spanning healthcare, enterprise analytics, and real-time trading products. They have owned React/TypeScript dashboard surfaces end-to-end, including a hospital patient dashboard that cut latency by 50%, and have also shaped backend WebSocket contracts to make real-time systems scale.”

Harshal Sawant

Screened

Senior AI Engineer specializing in LLMs, RAG, and MLOps on multi-cloud

8y exp

“Built and productionized a secure internal RAG-based AI assistant (LangChain/FastAPI/FAISS on GCP), tackling real-world issues like latency, retrieval speed, and hallucinations—delivering 25% faster retrieval and 99.9% uptime. Also implemented scalable, reliable ML retraining orchestration with AWS Step Functions/SageMaker/Lambda and partners closely with compliance analysts to iteratively refine prompts and outputs to meet governance standards.”

“Built and owned end-to-end production Conversational AI and RAG systems at Nike for customer support and product search, with strong evidence of measurable impact. Combines LLM product thinking with solid platform engineering, including evaluation pipelines, monitoring, safety controls, and reusable FastAPI frameworks that improved both user outcomes and team velocity.”