Vetted OCR Professionals

Manas Agarwal

Screened

Junior Full-Stack Software Engineer specializing in Python APIs, React, and cloud AI integrations

Superior, CO2y exp

“Customer-facing software engineer who builds and deploys practical AI/RAG solutions (e.g., an AI assistant for searching billing PDFs) by deeply understanding support workflows and iterating with users. Demonstrates strong production instincts—quickly stabilizing peak-traffic API timeouts with caching/background jobs, then implementing durable fixes with proper monitoring and maintainable code practices.”

“Engineering/CTO-style leader with hands-on architecture experience who has driven end-to-end modernization of a manual antiques auction operation—building centralized web-accessible data systems, digitizing historical records via OCR/freelancers, and defining profitability-focused KPIs with an eye toward predictive modeling. Emphasizes provider-agnostic, containerized SaaS architecture to avoid vendor lock-in and has experience scaling a small engineering team with ownership-based culture and lightweight processes.”

Venkata Sai Bharath Sirigiri

Screened

Junior Robotics/Mechatronics Engineer specializing in EV charging communications and HIL testing

2y exp

“Embedded/EV charging test & validation engineer working across EVSE and EVCC products, specializing in CAN/DBC analysis, firmware deployment, and HIL testing. Built custom Python GUI tools (CAN explorer + configurable test scenario runner) to accelerate diagnostics and reproducibility, and has resolved high-stakes customer interoperability issues by pinpointing hardware/firmware edge cases. Actively looking to pivot into robotics, leveraging prior robotics projects (SLAM, path planning, vision/perception).”

Taruni Reddy Ampojwala

Screened

Mid-level GenAI Engineer specializing in LLM agents and RAG systems

Brooklyn, NY4y exp

“Built and deployed a production RAG-based LLM assistant that answers day-to-day operational questions from internal PDFs/SOPs, with strong emphasis on data consistency (metadata versioning, confidence thresholds, conflict handling) and low-latency retrieval at scale. Experienced designing and orchestrating multi-agent LLM workflows (retrieval/validation/generation) and pipeline orchestration for ingestion/embedding/vector-store updates, plus iterative delivery with non-technical operations/business stakeholders.”

MANOGNA VADLAMUDI

Screened

Junior AI Engineer specializing in LLM evaluation, prompt engineering, and AI orchestration

Chicago, IL1y exp

“LLM workflow builder who has deployed a personalized GPT experience (including Delphi AI-based knowledge ingestion) and built a LangChain/LangGraph job-aggregation pipeline that ingests, normalizes/dedupes, filters, then uses an LLM to rank and summarize matches. Emphasizes production reliability with structured outputs, retries/fallbacks, metric-driven evaluation, logging/prompt versioning, and A/B testing, and collaborates with non-technical stakeholders through demo-driven iteration.”

“Product-minded full-stack engineer with experience in fintech identity verification and industrial analytics, focused on turning repeated operational pain points into reusable platforms. Built real-time KYC/KYB dashboards, secure cross-platform web components, and a multi-tenant workflow engine that cut onboarding from 2 weeks to 1 day while materially improving conversion, reliability, and developer speed.”

“Built and deployed a production AI accessibility platform that turns chart and image-based graphs into real-time audio narratives for visually impaired users. Implemented a ResNet-based CV + OCR + NLP + TTS pipeline and improved performance through preprocessing, Redis caching, and Kubernetes autoscaling/rolling updates on AWS to handle traffic spikes with no downtime.”

Dhruv Bansal

Screened

Intern Software Engineer specializing in backend systems and distributed data pipelines

San Francisco, CA1y exp

“LLM engineer with production experience building end-to-end document processing workflows that unify layout analysis, OCR, and downstream LLM reasoning. Has implemented reliability features (retries, robust error handling, OpenTelemetry logging) and built agentic systems using LangChain/CrewAI, including a student research-paper assistant, while collaborating closely with PMs and non-technical end users to reduce technical debt and simplify architectures.”

Vishnu Priyan Sellam Shanmugavel

Screened

Mid-Level Applied AI Engineer specializing in LLM services, RAG, and OCR/NLP extraction

Arlington, VA4y exp

“Backend/platform engineer who built and evolved a large-scale healthcare document processing system (OCR + LLM orchestration) in Python/FastAPI on Google Cloud (Cloud Run, GCS, Firestore), processing ~1.5M files per batch and tens of millions overall. Emphasizes reliability and operational safety via deterministic IDs, idempotent state machines, strong observability, and self-healing reconciliation, plus disciplined migrations using dual-run validation and incremental rollouts.”

Jackie Nguyen

Screened

Senior Software Engineer / Technical Lead specializing in cloud-native microservices

Overland Park, KS8y exp

“LLM/agentic-systems practitioner who shipped a recruiting resume-assistant from prototype to production, tackling hallucinations and multi-format document ingestion (PDF/images with OCR). Strong in real-time workflow debugging (logs/traces, reproducing prod issues) and pragmatic mitigation (feature flags), and helped drive customer adoption by presenting impact data and creating educational materials.”

“Built production LLM/agent systems for procurement and contract spend controls, including a proactive contract value leakage detection platform that moved an organization from reactive audits to pre-payment rejection. Combines multi-agent orchestration (Semantic Kernel/LangChain/AutoGen), document AI benchmarking (Textract vs Azure DI), and MLOps/testing (MLflow, QTest/Pytest) with strong security practices (RAG-grounded responses to prevent prompt injection). Integrated anomaly alerts directly into SAP SES workflows and Power BI dashboards, citing ~$38M leakage addressed across large spend environments.”

“Built and owned a customer-facing Document Intelligence Service for legal contract analytics at Noasis Digital, delivering extraction/summarization with careful accuracy controls (confidence thresholds, versioned deployments, production logging). Also developed a React/TypeScript document review app and internal QA dashboard, and has hands-on microservices experience with async messaging (RabbitMQ), timeout tuning, and centralized structured logging for reliability at scale.”

“Product-minded full-stack engineer with hospitality tech experience who owned and scaled a multi-region guest verification/check-in workflow (ID/passport scanning, OCR, and government submissions) and built internal tools that cut manual entry up to 80%. Also built a React/TypeScript + FastAPI RAG “second brain” with async ingestion workers and an event-driven e-folio email microservice hardened with idempotency and retries.”

“Built and deployed a production AI-powered personalized learning platform (Django + FastAPI) featuring an LLM+RAG tutoring assistant and automated grading. Demonstrates strong applied LLM reliability engineering (structured JSON outputs with Pydantic validation, hallucination control via FAISS-based RAG thresholds and refusals) plus scalable async microservice design and Airflow-orchestrated ETL across AWS/GCP.”

Swapnil Sanjay Pawar

Screened

Junior Full-Stack Software Engineer specializing in GenAI and web platforms

Atlanta, GA2y exp

“AI/software engineer with hands-on experience deploying an LLM-powered quiz generation platform for students, integrating Python services with Gemini APIs plus frontend and database components. Emphasizes production-grade reliability through observability, schema validation, async processing, and performance tuning under high concurrency, and has collaborated with product/operators (e.g., at Colombo AI) to translate real-world constraints into scalable technical solutions.”

Tharun Chowdary Malepati

Screened

Mid-level AI/ML Engineer specializing in GenAI, NLP, and production MLOps

5y exp

“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”

“AI/ML engineer with hands-on experience owning production deployments from discovery through post-launch stabilization, including real-time computer vision/OCR systems and LLM-powered RAG workflows. Stands out for translating messy customer workflows into reliable backend services, debugging non-deterministic retrieval issues, and hardening AI systems with validation, monitoring, and human-review fallbacks.”

“Led a government smart city deployment where success depended less on pure engineering and more on navigating policy, budget, and operational constraints. Built phased, cost-conscious systems combining data pipelines, on-prem AI, OCR, and human-in-the-loop workflows to deliver stable production outcomes and make ambiguous real-world data more controllable at scale.”

“Built a production-grade clinical and insurance document AI system in a HIPAA/PHI-regulated environment, taking it from experimentation through Azure deployment, monitoring, and iterative improvement. Stands out for translating RAG/LLM research into reliable microservices with strong safety controls, drift monitoring, and human-in-the-loop workflows that cut manual review time by 60-70%.”

Kathan Patel

Screened

Mid-level Generative AI Developer specializing in Python and LLM applications

5y exp

“Currently working on Kavia AI, an end-to-end AI coding platform that lets users generate enterprise applications from prompts and existing codebases via SCM integrations. The candidate has hands-on experience across the GenAI stack—prompt engineering, LangGraph-based multi-agent orchestration, RAG, knowledge graphs, FastAPI, and AWS monitoring—with a focus on making software creation accessible to non-technical users.”