Adam is a senior full-stack engineer with deep expertise in Python, React, TypeScript, and GenAI/ML tooling. He demonstrates strong architectural and system design skills, with hands-on experience in building AI-driven products, SaaS platforms, and scalable cloud solutions. Adam is recognized for his product-first mindset, clear communication, and pragmatic technology selection. He is recommended for backend, cloud/DevOps, and GenAI-heavy roles.
14 years of commercial experience in
AI
Analytics
Business intelligence
Consulting services
Data analytics
Machine learning
Marketing
Medtech
Real estate
Scientific research
SaaS
Gaming software
Web development
Main technologies
Python
5 years
React
10 years
Typescript
5 years
JavaScript
20 years
Additional skills
Next.js
Django
AI
ONNX
FFmpeg
Docker
PostgreSQL
LLM
Ruby on Rails
AWS
DynamoDB
Node.js
Ruby
React Native
FastAPI
Voice AI integration
LLM integration
AI agent development
Claude LLM
LangChain
LangGraph
Rust
Direct hire
Possible
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Experience Highlights
CEO/CTO
Dec 2025 - Jul 20266 months
Project Overview
Client & Stakeholders: Acted as Founder/CEO/CTO, engaging directly with target PC gamers and streaming content creators to define ultra-low latency requirements and local voice control expectations.
Business Problem & Ambiguity: Cloud-based voice AI introduces latency and privacy risks while consuming heavy system bandwidth. Gamers needed a lightweight, zero-cloud-overhead voice control tool operating in high-noise environments without dropping frame rates.
End User: Competitive PC gamers and streaming content creators.
Solution Built: A local-first, real-time speech-to-text AI system designed for gamers, enabling low-latency voice commands and interactions in fast-paced, noisy gaming environments. Adam designed and built the application using Rust, React, Tauri, and ONNX Runtime, developing the full local AI pipeline for streaming audio, wake-word detection, transcription, and intent recognition.
Measurable Outcome: Achieved sub-second latency and high transcription accuracy while maintaining minimal CPU and memory overhead during continuous background operation.
Project gallery:
Responsibilities:
Designed and built the application architecture using Rust, React, Tauri, and ONNX Runtime;
Engineered a local-first, real-time speech-to-text pipeline optimized for ultra-low latency;
Trained and fine-tuned Whisper for gaming-specific terminology, vocabulary, and speech patterns;
Developed and trained intent-recognition models for mapping spoken language to gaming-specific actions;
Implemented streaming audio capture and processing for continuous voice interactions;
Built wake-word detection for near-instant voice activation;
Developed domain-specific post-processing and correction layers to improve transcription accuracy;
Implemented real-time intent mapping and command execution;
Optimized local inference for minimal CPU and memory usage during continuous background operation;
Built cross-platform infrastructure for efficient local AI inference and deployment;
Optimized the system for accurate speech recognition in noisy gaming environments.
Project Tech stack:
React
ONNX
AI
Voice AI integration
Rust
Windows
Senior Product Engineer
Feb 2025 - Nov 20259 months
Project Overview
Client & Stakeholders: A YC-backed platform using AI to automate research and report-generation workflows for practitioners. Worked directly with psychological practitioners and researchers at Harvard’s Psychology Department, translating highly ambiguous assessment workflows into explicit technical specs.
Business Problem & Ambiguity: Mental health practitioners and researchers spent excessive manual hours processing unstructured clinical assessments, physical documents, and transcriptions into structured research reports.
End User: Clinical psychologists, academic researchers, and healthcare practitioners.
Solution Built: A HIPAA-compliant AI research automation platform that extracts, structures, and synthesizes clinical assessments into formal reports.
Measurable Outcome: Drastically reduced manual processing turnaround times for complex assessment reports and enabled conversational natural language analysis across clinical datasets.
Project gallery:
Responsibilities:
Worked directly with practitioners and Harvard’s psychology department to understand workflows, identify opportunities for automation, and translate ambiguous requirements into technical solutions;
Designed and built full-stack AI features using Python, FastAPI, React, LangChain, and LangGraph;
Developed and shipped agentic workflows that transformed assessment data and research materials into structured reports;
Integrated Claude and ChatGPT APIs for report generation, reasoning, and conversational interaction with data;
Implemented OCR pipelines using localized models to extract and structure information from assessment documents;
Integrated Deepgram for speech-to-text capabilities within practitioner workflows;
Built conversational interfaces that enabled practitioners to query and analyze assessment datasets using natural language;
Designed and implemented HIPAA compliant workflows for handling sensitive healthcare data, incorporating secure data processing, privacy controls, and compliance requirements across the application stack;
Rapidly prototyped and iterated on AI workflows based on feedback from practitioners and research stakeholders;
Translated domain-specific requirements into production AI features while adapting solutions as requirements evolved;
Owned features from technical discovery and architecture through implementation and delivery;
Optimized AI workflows to reduce manual processing and improve report-generation turnaround times.
Project Tech stack:
Python
React
Typescript
AWS
Claude API
Voice AI integration
Senior Product Engineer
Dec 2024 - May 20254 months
Project Overview
Client & Stakeholders: Embedded directly with Warner Bros. creative and technical marketing teams to translate film promotion goals into a high-concurrency production architecture.
Business Problem & Ambiguity: Needed a multi-lingual, global campaign platform capable of dynamically transforming raw user selfies into personalized, film-themed video content while supporting massive concurrency spikes upon launch.
End User: Global movie fans promoting Beetlejuice Beetlejuice.
Solution Built: An international web experience that transforms user selfies into AI-rendered movie characters embedded inside shareable video clips.
Measurable Outcome: Successfully localized across multiple languages and scaled to support millions of global users in a short post-launch window.
Project gallery:
Responsibilities:
Participated in initial product discovery and technical planning, translating Warner Bros. campaign goals into technical requirements and a production architecture;
Built the backend from the ground up using Python and FastAPI;
integrated the BRIA AI API and prototyped the AI image-generation pipeline;
Built an automated video-generation pipeline using FFmpeg;
Designed and developed AWS infrastructure to support the personalized user experience;
Collaborated directly with Warner Bros. teams to iterate on creative and technical requirements;
Scaled and localized the platform for deployment across multiple countries and languages;
Optimized the system to support high-volume production traffic and millions of users in a short period.
Project Tech stack:
FFmpeg
Python
AWS
FastAPI
AI API integration
Chief Technology Officer
Sep 2022 - Dec 20242 years 3 months
Project Overview
Client & Stakeholders: Operated as CTO leading technical architecture, direct client sales, and customer success directly with dental practice owners and office managers.
End User: Dental office managers, receptionists, and practice owners.
Solution Built: End-to-end dental office management SaaS featuring workflow automations, business analytics, and operational automation routines.
Measurable Outcome: Scaled the platform to over $1M in ARR within two years while leading a lean engineering team.
Responsibilities:
Built and scaled a SaaS platform for dental office management to over $1M in revenue within two years;
Played a key role across the full product lifecycle, including product development, team leadership, sales, and customer success;
Helped guide a small team while working directly with customers to refine features and drive adoption.
Project Tech stack:
LLM
PostgreSQL
Python
React
Ruby on Rails
React Query
React Flow
Senior Software Engineer
Oct 2020 - Dec 20211 year 2 months
Project Overview
Product: A SaaS platform enabling enterprises to build, test, and deploy automated customer service voice agents.
Target Users: Customer service leads, business operations managers, and software developers.
Responsibilities:
Helped create new features for clients and the product;
Increased front-end and back-end application performance by optimizing rendering, removing unnecessary code, refactoring existing code, and implementing caching;
Built new data-processing pipelines for both sending and receiving data;
Built a CLI tool to increase developer productivity on repetitive tasks;
Iterated on existing features across the full-stack application.
Project Tech stack:
AWS
Docker
DynamoDB
Node.js
Python
React
Typescript
TypeORM
Senior Product Engineer
Dec 2019 - Mar 20202 months
Project Overview
Client & Stakeholders: Partnered directly with engineering and product teams at Samsung and obé to build a novel TV app within strict platform hardware constraints.
Business Problem & Ambiguity: Porting web/mobile live-streaming fitness experiences to a TV OS while incorporating never-before-integrated Samsung Health SDK hardware telemetry.
Solution Built: A fitness streaming application that brought obé’s live and on-demand workouts to Samsung Smart TVs.
Measurable Outcome: Successfully shipped one of the first integrations of the Samsung Health SDK into a Smart TV fitness app across the global Samsung TV ecosystem.
Responsibilities:
Built the frontend and backend for the Samsung Smart TV application;
Developed the TV experience using React and Samsung’s TV SDKs on top of the Chrome-based platform;
Implemented the first integration of Samsung Health SDKs into the TV fitness experience;
Integrated obé’s live and on-demand fitness content and services;
Collaborated directly with Samsung and obé engineering and product teams throughout development;
Built backend APIs and services supporting the TV application;
Optimized the application for TV-specific navigation, performance, and hardware constraints;
Debugged and resolved platform-specific issues across the React application, Samsung SDKs, and TV environment.
Project Tech stack:
React
Android
Android Studio
JavaScript
Keep in mind, the experience summary might exclude non-relevant projects
Languages
Spanish
Intermediate
English
Advanced
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