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Embedded AI Engineer who designs, builds, and deploys production AI systems for B2B clients in private equity, lending, real estate, and SaaS, bridging business needs with technical execution using LLMs, RAG, and agent frameworks.
Builds and maintains data pipelines for building systems and IoT devices, develops AI models for anomaly detection and predictive maintenance, and supports cloud-based analytics using Python, SQL, and Docker.
Lead a team building AI-assisted Java services with Spring Boot, Angular frontends, and AWS infrastructure, using tools like Claude Code to streamline development and delivery.
Build and own AI-native marketing and investor-relations infrastructure: a Next.js website, internal brand/IR tools, and agentic workflows that automate content, reporting, and compliance for a cleantech startup.
Build and deploy AI agents for government clients, designing scalable agentic systems with guardrails and governance to automate public service workflows.
Build and deploy AI/Generative AI solutions using LLMs, RAG, and cloud platforms to drive insights and automation for Mastercard’s global operations.
Build and maintain scalable data/AI systems for JPMorgan’s finance platform, using Python, Databricks, AWS, and enterprise AI coding tools to deliver secure, audit-ready reporting.
Designs and implements AI-driven quality control processes for electronics manufacturing, using statistical methods and testing tools to ensure product precision and reliability.
Build and deploy generative AI systems using RAG, LLMs, and cloud-native MLOps on Azure, while mentoring teams to deliver scalable AI solutions across industries.
Build and run automated tests for AI-powered automotive software using Python, Selenium/Playwright, and CI/CD pipelines to validate AI outputs and system reliability.
Build and deploy enterprise-scale AI systems (RAG, agentic workflows, LLMs) to automate workflows and improve resilience for a global financial markets infrastructure provider.
Build and deploy AI features for wearables, including on-device models, RAG pipelines, and AI agents, while collaborating with cross-functional teams.
Build production-grade full-stack software that integrates with agentic AI systems, using AI coding assistants daily and LLM APIs in live code.
Build and architect enterprise-grade AI systems, including LLM-driven agents, RAG pipelines, and multi-agent orchestration, while designing context layers and ensuring security and scalability.
Design and implement enterprise-grade AI architectures, including multi-agent systems, RAG pipelines, and model routing, while enforcing security, governance, and cost controls for large-scale deployments.
Fine-tunes and adapts large language models for domain-specific use cases using Python, AWS, and MLOps pipelines to improve accuracy and contextual relevance.
Lead the North America Commercial AI strategy, building and deploying LLM/agentic AI solutions for patient finding, HCP engagement, and commercial workflows in a biopharma company.
Build and integrate AI features (LLMs, agents, RAG) into existing products to automate data extraction, QA/QC, and infrastructure asset recognition for civil/transportation use cases.
Build and harden agentic AI systems that automate underwriting and claims workflows, integrating with legacy insurance platforms while balancing latency, cost, and reliability.
Build and ship AI-powered features end-to-end for a UK security-training platform, from LLM prototypes to production code, owning discovery through iteration.
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