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Vetted LangChain Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in healthcare and fintech AI systems
Mid-level Machine Learning Engineer specializing in Bayesian inference and reinforcement learning
Senior Full-Stack Python Developer specializing in cloud, data platforms, and GenAI
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-level Data Scientist specializing in GenAI, LLMs, and MLOps
Senior Full-Stack Software Engineer specializing in cloud platforms and AI integration
Staff AI & Data Engineer specializing in LLM systems and real-time data platforms
Senior Software Engineer specializing in cloud, data platforms, and LLM/RAG applications
Mid-level AI/ML Engineer specializing in cloud MLOps and GenAI for fraud detection
Mid-level Data Scientist specializing in FinTech and product analytics
Senior AI Engineer specializing in healthcare and FinTech AI systems
Senior Applied AI Engineer specializing in LLMs, RAG, and computer vision
Executive Product & Technical Services Leader specializing in AI, Crypto, and FinTech
Senior AI & Systems Architect specializing in ML infrastructure and FinTech
Aaditya Voruganti
Junior AI & Software Engineer specializing in robotics and ML infrastructure
“Robotics engineer from UIUC’s Intelligent Motion Lab who led the perception stack for a humanoid robotic nurse, fusing camera/LiDAR/IMU on NVIDIA Jetson Orin for real-time localization and scene understanding across six robots. Deep expertise in ROS 2 and edge ML optimization (TensorRT, CUDA, zero-copy), delivering major latency/throughput gains (10 FPS to 22+ FPS) and building fault-tolerant pipelines with gRPC offloading and real-time reliability practices.”
Kerui Lu
Intern Software Engineer specializing in cloud, full-stack, and distributed systems
“Interned at SLB and owned an end-to-end GenAI chatbot deployment for a finance team, including invoice PDF data extraction and an LLM-driven layer (LangGraph/LangChain) that translated natural language to SQL and returned results in natural language. Validated LLM JSON outputs against benchmarks using DeepDiff and deployed the solution via Docker to Kubernetes, managing pods with k9s.”
Jagadeesh Kakamolu
Mid-level Software Engineer specializing in backend, cloud, and AI systems
“Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.”
Balpreet Kaur
Junior Machine Learning Engineer specializing in LLMs and data pipelines
“Research Extern at Google DeepMind and former AWS Software Development Engineer Intern with a strong focus on practical, trustworthy AI engineering. Built a multi-agent RAG system for personalized news headline generation using a fine-tuned Flan-T5 model, parallel critic agents, FAISS retrieval, and style embeddings, while also leading a 3-person team on the project.”
Tianyi Wang
Entry-Level Backend/Cloud Engineer specializing in distributed systems and AI platforms
“Full-stack engineer with deep serverless AWS experience who built VidToNote, an AI video analysis platform, end-to-end using Next.js App Router/TypeScript and an event-driven pipeline (API Gateway, Lambda, DynamoDB, S3, Step Functions, SQS). Strong on production reliability and observability (CloudWatch, X-Ray, structured logging), plus data/analytics work in Postgres with measurable query optimizations and durable LLM evaluation workflows. Amazon background; integrated 22 AWS services and completed AWS Solutions Architect Professional certification within a month.”