Anhedral
Chief Technology Officer
2025 - Present (Full-time)
- Co-founded Anhedral and leads development of Anhedral Core, the platform underpinning the company's agent-driven products.
- Owns technical strategy, architecture, and engineering execution across product lines, translating product goals into reliable systems.
- Designs and builds software factories that coordinate AI agents across the software development lifecycle.
- Builds autonomous agents that operate software interfaces on users' behalf, with an emphasis on dependable execution and recoverable workflows.
Tech: Computer-use agents, browser control, LLM harnesses, software factories, full-stack systems
Cognition Labs
Lead Software Engineer
2025 - Present (Full-time)
- Leads engineering for CogniLens across iOS, Android, web, browser extension, and AR/XR experiences for neurodiverse readers.
- Owned end-to-end system architecture across frontend clients, backend APIs, authentication, role-based access control, subscriptions, and relational data models.
- Architected and shipped a developer-facing API enabling internal and external integrations while enforcing tenant isolation and security boundaries.
- Serves as technical owner across engineering, product, and research, driving scope, prioritization, and delivery from concept through production.
- Translated neurodiversity accessibility research into shipped, user-facing functionality used in production environments.
- Supported production releases, CI/CD pipelines, and post-launch iteration, incorporating real-world usage signals to guide ongoing improvements.
Tech: Cross-platform mobile & web stacks, cloud APIs, relational databases, authentication & payments infrastructure, CI/CD, modern UI systems
LearnAIR (formerly Neesh AI)
Lead Software Engineer
2024 - 2025 (Full-time)
- Directed the end-to-end development and launch of a B2B AI chat platform adopted by paying customers.
- Architected a provider-agnostic, multi-LLM system, dynamically selecting models based on cost, latency, and capability constraints.
- Built retrieval-augmented generation (RAG) pipelines including document ingestion, chunking, embeddings, retrieval, and user-level personalization.
- Delivered core platform features including chat history, artifacts, folder hierarchies, role-based access control, subscriptions, and image generation.
- Led and mentored a small engineering team, setting technical direction, reviewing code, and unblocking delivery.
- Owned production reliability and iteration cadence, prioritizing features based on direct customer feedback and operational needs.
Tech: LLM application architecture, RAG systems, full-stack web development, workflow automation, team-scale engineering practices
SAP
Software Engineer
2024 (Contract)
- Developed a full-stack AI knowledge graph application using structured LLM outputs and deterministic pipelines.
- Collaborated with design and engineering teams to translate research goals into a functional production prototype.
- Conducted UX studies and iterated on system behavior based on qualitative user feedback.
- Contributed to work published in an IEEE research paper, bridging applied research and real-world system implementation.
Tech: Structured LLM pipelines, data-centric design, full-stack web systems, research-driven workflows
DXM
Software Engineer
2014 - 2025 (Part-time)
- Long-term contributor (10+ years) to DXM's AI and creative technology initiatives alongside academic and professional roles.
- Helped build an AI image generation platform serving brand and creative customers.
- Implemented and evaluated diffusion models and advanced prompt-engineering workflows.
- Supported early-stage startup efforts through rapid prototyping, demos, and technical direction during fundraising and customer pitches.
Tech: Generative image systems, diffusion models, prompt engineering, rapid prototyping
Ford Motor Company
Intern - UXD
2019 (Internship)
- Built simulation tooling to model autonomous driving scenarios for AV research.
- Created data pipelines for video transcription, labeling, and analysis to support research workflows.
- Operated in a research-focused environment emphasizing reproducibility, data quality, and experimentation rigor.
Tech: Simulation environments, data annotation pipelines, research tooling
