Vetted LangChain Professionals

“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 production LLM applications including a natural-language-to-read-only-SQL system focused on ambiguity handling and query safety (schema whitelisting, intent validation, confidence checks, deterministic execution). Experienced with LangChain-based, modular agent orchestration and RAG document QA for large PDFs, with a metrics-driven testing/evaluation approach and cross-functional delivery with marketing on an AI content recommendation/search tool.”

“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.”

“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.”

“Built and shipped production LLM agents for real-time, high-concurrency conversational systems, including a RAG-based pipeline with dynamic multi-provider routing and failover that achieved 99.99% reliability and sub-800ms latency. Also architected a UAV telemetry chatbot with tool-calling (anomaly detection/summarization), strict schema validation, and robust eval/monitoring loops, cutting tool-call errors by 30% and reducing operational costs by 90%.”

Rizwana Shaik

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native apps and AI copilots

Dallas, TX4y exp

“Internship project building and deploying a LLaMA-based, RAG-enabled copilot inside a Professional Services Automation platform, enabling natural-language navigation, text-to-SQL reporting, and project/resource/budget insights across multiple modules. Addressed real production issues like context drift and vague queries with hybrid search, metadata enrichment, and an intent classification/rewriting layer, orchestrated via Apache Airflow—ultimately cutting PMO reporting time by 40%.”

Ramya Jonnala

Screened

Principal/GenAI Engineer specializing in LLMs, RAG, and MLOps

Plano, TX9y exp

“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”

Thota Rajkumar

Screened

Junior Cloud & AI Infrastructure Engineer specializing in Agentic AI and AWS

San Jose, CA2y exp

“Built and deployed a production AI career-advice agent designed to combat unreliable/generic LLM guidance by grounding outputs in retrieval-first RAG over resumes/job/hiring data, with multi-step reasoning, structured memory, and evidence-only prompting to reduce hallucinations. Implemented the system with LangChain/Python and deployed on AWS as scalable microservices orchestrated via REST and asynchronous calls, iterating closely with career coaches and students.”

HarshaVardhanRao Vemuganti

Screened

Junior AI/ML Engineer specializing in Generative and Agentic AI

Lafayette, Louisiana4y exp

“Built and deployed a production-grade LLM agent for credit management and accounts receivable automation, integrating ERP/MySQL data via a RAG pipeline and exposing services through FastAPI with Pydantic-validated outputs on AWS Bedrock. Emphasizes reliability and compliance for financial operations using schema validation and human-in-the-loop review, reporting ~32% reduction in manual work and ~41% improvement in response time/reliability.”

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.”

“Full-stack engineer who has owned both institutional and personal products end-to-end, including Rutgers' myCommunity platform used by 70,000+ students. Particularly strong in production systems, data synchronization, authentication, and third-party API integrations, with a pragmatic approach to shipping, observability, and UI modernization.”

“AI/ML engineer with 9+ years of experience building production recommendation and LLM systems end-to-end, from experimentation through deployment, monitoring, and retraining. Stands out for combining strong MLOps discipline with practical GenAI/RAG implementation, including measurable impact such as ~25% higher engagement on an e-commerce recommender and nearly 30% faster knowledge retrieval from internal documents.”

Ankit Gupta

Screened

Junior Software Engineer specializing in backend systems and AI applications

India2y exp

“Engineer who independently shipped pagination for a global financing platform handling large financial datasets, including accounts with roughly 25,000 securities. Stands out for using AI pragmatically—accelerating boilerplate while rigorously reviewing data contracts, ordering assumptions, access control, and production reliability in a financial domain.”

“Full-stack and AI product engineer with strong accessibility and voice-interface experience in senior living, building systems for older adults where trust and usability are critical. Has shipped React/TypeScript and .NET MAUI products, productionized Azure OpenAI features, built RAG-based research tools, and improved both product outcomes and technical performance with measurable impact.”

Faisal Hayat

Screened

Senior Python Full-Stack Engineer specializing in AI-powered backend systems

Lahore, Pakistan6y exp

“Backend-leaning full-stack engineer with startup experience building AI-powered products and ERP/SaaS platforms. They’ve delivered Python/FastAPI/Django and React systems on AWS, including an AI document processing platform and business workflow tools used by thousands of users, with strong hands-on depth in database optimization and production operations.”

“Full-stack/backend-leaning engineer who owned Shoptaki's Smart ID authentication platform end to end, building a centralized identity system that secured four services and removed duplicated auth logic. Also introduced and operationalized Claude Code in a TypeScript microservices environment, using prompt refinement, CI, and code review guardrails to improve development speed without compromising architecture or security.”

“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%.”

Emma Choudhary

Screened

Senior Full-Stack Software Engineer specializing in Python, Django, and Generative AI

United States6y exp

“Backend/data engineer with hands-on production experience building partner-facing Python APIs (FastAPI, Celery, Postgres/Redis) and AWS serverless data platforms (Lambda, SQS, Step Functions, Glue). Emphasizes reliability and governance—JWT tenant-scoped auth, secrets/config hygiene, data-quality quarantine, and incident ownership—plus measurable SQL tuning that eliminated timeouts and stabilized reporting workloads.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”

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.”