Awais Butt

Lead Software Engineer with 8+ years building scalable full-stack AI solutions in regulated healthcare and life sciences environments. Skilled in designing AI-powered agents, intelligent automation, and cloud-native applications using modern JavaScript, TypeScript, Python, and Node.js. Strong collaborator with excellent writing and documentation skills. Focused on delivering robust, compliant software through technical leadership and strategic thinking.

Senior AI Engineer at BookYolo (2025-09 – 2026-08)

• Built AI-powered property and travel intelligence features using TypeScript, Node.js, and Python, integrating LLM agents for real-time property evaluation and risk analysis.
• Designed full-stack AI agent workflows with LangChain and OpenAI, enabling automated property comparison and personalized travel recommendations.
• Developed RESTful APIs and backend services in Python and Node.js for AI inference, data retrieval, and product integrations, deployed on AWS with Docker and CI/CD pipelines.
• Implemented containerized microservices architecture using Docker and Kubernetes, improving scalability and deployment reliability for AI services.
• Led technical initiatives in a startup environment, mentoring engineers on AI architecture, full-stack development, and production deployment best practices.
• Collaborated with product and engineering teams to define AI roadmap, ensuring alignment with business goals and regulatory compliance for data handling.
• Built data ingestion and enrichment pipelines using cloud-native tools (GCP Pub/Sub, BigQuery), processing structured and unstructured data for AI models.
• Enhanced LLM reliability through prompt engineering, rigorous evaluation, and hallucination analysis, ensuring high-quality outputs in production.

Lead AI Engineer at Gspec Technologies (2023-12 – 2026-04)

• Led distributed engineering teams in designing AI-powered agent systems for healthcare and life sciences, ensuring compliance with HIPAA and GxP regulations.
• Developed full-stack AI applications using TypeScript, Node.js, and React, integrating LLM agents for intelligent automation and clinical decision support.
• Built RESTful backend services with Python, FastAPI, and Node.js, deployed on AWS with Docker, Kubernetes, and GitHub Actions CI/CD pipelines.
• Architectured scalable microservices for AI inference, data retrieval, and workflow orchestration, handling sensitive healthcare data with RBAC and encryption.
• Implemented AI agent workflows using LangChain, LangGraph, and OpenAI, enabling automated patient data analysis and treatment recommendation pipelines.
• Designed and deployed containerized solutions on AWS ECS and GCP Cloud Run, reducing deployment time and improving system reliability.
• Developed data ingestion and ETL pipelines for unstructured healthcare data (clinical notes, lab results) using Python, Pandas, and BigQuery.
• Built monitoring and observability dashboards for AI model performance, drift detection, and operational metrics in regulated environments.
• Collaborated with product managers and compliance officers to define AI roadmaps, ensuring alignment with regulatory requirements and business objectives.
• Mentored junior engineers on full-stack development, AI best practices, and secure coding standards in a regulated healthcare context.
• Migrated legacy monolithic applications to cloud-native, containerized architectures, improving scalability and maintainability.
• Developed intelligent automation workflows using n8n and event-driven architecture, reducing manual data processing by streamlining operational tasks.
• Worked in a dynamic startup consultancy, delivering AI solutions for healthcare, fintech, and retail clients under tight deadlines.

Senior Software Engineer at PCS Research Group LLC (2022-11 – 2023-12)

• Developed automation scripts using Python and Selenium for large-scale data collection from public sources.
• Built Django-based web applications with PostgreSQL for data management and user authentication.
• Designed RESTful APIs for data ingestion and reporting, supporting business analytics.
• Implemented data processing pipelines for cleaning and transforming raw data into structured formats.
• Collaborated with team members to deploy applications on cloud infrastructure using Docker.
• Created dashboards for operational metrics using Python and visualization libraries.
• Maintained code quality through version control and code reviews.

Software Engineer at MedRisk (2019-07 – 2022-08)

• Developed healthcare applications for operational analytics using Python and Django, improving data-driven decision-making.
• Built interactive dashboards and reporting tools to visualize patient outcomes and operational efficiency.
• Processed and analyzed healthcare data using SQL and Python, ensuring compliance with data privacy standards.
• Supported A/B testing and workflow optimization efforts to enhance application performance.
• Collaborated with engineering and business teams to deliver scalable software in a regulated healthcare environment.
• Contributed to backend modernization by migrating legacy code to modern Python frameworks.
• Monitored application health and performance using logging and basic observability tools.

Bachelor of Science in Computer Science – Penn State University (2016)