Vetted R Professionals

“AI/software engineer with experience at Visa building a real-time transaction fraud/risk scoring microservice in the card authorization path (Python, Kafka, Kubernetes on AWS) with strict 120–150ms latency constraints and reason-code outputs for downstream decisioning. Owns ML backend end-to-end (data/feature engineering, model training, deployment) and has demonstrated production reliability work including latency spike mitigation, SLO-based observability, drift monitoring, and safe fallbacks to rule-based decisions.”

“Siemens AI engineer who shipped production multi-agent LLM systems across cybersecurity and sustainability, including a vulnerability automation agent that cut manual work 70%. Deep in orchestration (LangGraph supervisor-worker state machines), reliability engineering (async fault tolerance, retries, spike handling), and rigorous evaluation (offline benchmarks, LLM-as-a-Judge improving label agreement 28.9%) with measurable production guardrails.”

“AI/ML engineer who has shipped production AI systems end-to-end, including an automated multi-channel (Gmail/WhatsApp/voice) candidate interviewing workflow and an enterprise RAG knowledge search platform. Demonstrates strong production rigor (monitoring, A/B tests, guardrails, schema validation, shadow testing) with quantified impact: ~60–70% reduction in interview evaluation time and ~20–30% relevance gains in RAG retrieval.”

“GenAI/LLM engineer who architected and deployed a production RAG “research assistant” for JPMorgan Chase’s regulatory compliance team, focused on safety-critical behavior (mandatory citations, refusal when evidence is missing). Deep hands-on experience with LlamaIndex, Pinecone, Hugging Face embeddings, LangGraph agent workflows, and metric-driven evaluation (golden sets, TruLens), including a reported 28% relevancy lift via cross-encoder re-ranking.”

“Backend/distributed-systems engineer with AI infrastructure experience who built an AI-driven video generation platform, focusing on an asynchronous FastAPI-based orchestration layer between user APIs and heavy inference services. Strong in production instrumentation and latency/concurrency optimization; actively learning ROS 2 but has not yet worked on physical robotics or ROS-based deployments.”

“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.”

“Firmware architect/lead engineer for automotive LiDAR sensors, designing RTOS-based, layered firmware and solving high-throughput real-time constraints using DMA and lock-free buffering. Built ROS nodes to bridge embedded sensor output to higher-level perception (point clouds, diagnostics, configuration) while isolating real-time logic in firmware. Established an end-to-end CI/CD pipeline with GTest unit tests plus SIL/HIL automation and Dockerized build/test environments.”

“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.”

“Built and deployed a production LLM-powered decision-support system for supply-chain planners that explains demand forecast changes using grounded retrieval from sales, promotion, inventory, and supplier data. Implemented strict anti-hallucination guardrails and latency optimizations, deployed as a real-time AWS API with monitoring, and reported ~15% forecast accuracy improvement and ~12% supply-chain risk reduction. Experienced orchestrating data/ML/LLM workflows with Airflow, LangChain/LangGraph-style patterns, and AWS Step Functions while partnering closely with non-technical business users via demos and example-based requirements.”

“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.”

“University of Michigan MDP / Atombots lab robotics engineer leading perception and sensor integration for multi-agent quadruped wheel-legged robots. Implemented and optimized RTAB-Map SLAM on Jetson Nano using Unitree L2 LiDAR + Intel RealSense D435i, including custom ROS 2 synchronization and TF2 calibration work; now building Apriltag-based tracking for multiple micro-robots to support decentralized swarm behavior research.”

“Completed an Amazon externship building a GPT-4 + RAG pipeline to summarize themes from hundreds of employee reviews for workforce analytics aimed at improving warehouse retention. Emphasizes production-readiness through labeled-data evaluation, source attribution for explainability, human-in-the-loop review, and rigorous data cleaning/observability to debug real-world LLM workflow issues.”

“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”

“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”

“Operations and customer-facing leader with deep last-mile logistics expertise from running a critical extra-large Amazon logistics hub end-to-end (inventory accuracy, throughput, yard efficiency), including scalable process improvements adopted across Amazon XL sites. Strong cross-functional and partner management (DSPs/carriers, engineering ops) with rapid incident resolution and VOC-to-product translation (geofence/map fixes). Also demonstrates land-and-expand growth motion from Cisco, expanding a standardized software platform across multiple global sites.”