Staff AI/ML Engineer
Resume:
Chris (JunQing) Ma
Staff AI/ML Software Engineer
San Jose, CA
*******.**@*****.***
SUMMARY
Staff AI Software Engineer at ServiceNow working to build autonomous AI systems. Unlike a traditional engineering team, I work in a lab where we explore, innovate and productize bleeding edge research related to GenAI. building and shipping enterprise Al solutions directly with customers. I work hands-on with product, engineering, and business teams to design, prototype, and deliver systems that turn LLMs and applied ML into reliable production outcomes. Previously at BairesDev, I developed and deployed full-stack generative Al applications across sectors including legal services and healthcare, while mentoring engineers and leading technical deep dives. I work end-to-end across software engineering and machine learning, using Python, JavaScript (React), SQL, cloud platforms, and modern LLM/ML tooling. Always open to connect and collaborate!
SKILLS
●Languages: JavaScript, TypeScript, Python, Java, SQL, C++, C#, Scala
●AI & NLP: OpenAI API, Claude, Gemini, LLM, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), Prompt Engineering, Vector Databases (Pinecone, ChromaDB), Semantic Search, AI Chatbots, Function Calling, Model Context Protocol (MCP)
●Frontend: React, Next, Angular, HTML5, CSS3, JavaScript, TypeScript, Tailwind
●Backend: Node.js, Express.js, Django, REST APIs, Microservices, Distributed Systems
●Cloud & DevOps: AWS (EC2, S3, VPC), Docker, CI/CD, Linux, Git, Jenkins, Kubernetes
●Databases: MySQL, Oracle, SQL, NoSQL, PostgreSQL, MongoDB, Kafka, Spark, Pandas, Numpy
●Architecture: API Design, Microservices, Distributed Systems, Multi-tenant SaaS, Performance Optimization
●Practices: Agile, Code Reviews, Mentoring, Unit Testing
EXPERIENCE
ServiceNow, Remote - Staff AI Software Engineer
Jul 2023 - Present
●Working in Platform Labs working on bleeding edge Agentic AI automation solutions. We build everything from the ground up, move fast and deliver amazing products to market.
●Designed and delivered AI-enabled enterprise applications using React, TypeScript, Python FastAPI, LangChain, RAG pipelines, and AWS cloud services, supporting scalable workflow automation and enterprise AI solutions.
●Developed production-grade LLM integrations using OpenAI, Claude, and Gemini APIs with prompt engineering, model evaluation frameworks, retrieval optimization, and MCP-based tool integrations.
●Built healthcare-focused AI solutions including claims summarization, clinical entity extraction, and NLP pipelines using Transformers, spaCy, PyTorch, and secure enterprise data architectures.
●Implemented cloud-native architectures using Docker, AWS ECS, S3, background workers, and CI/CD automation for reliable enterprise application deployment.
●Implemented secure AI architectures handling enterprise-sensitive data with PII/PHI protection, audit logging, encryption, guardrails, and compliance-focused controls.
●Implemented model evaluation, drift detection, anomaly detection, and automated retraining workflows, improving production observability and operational reliability for AI systems.
●Worked directly with enterprise customers to troubleshoot application behavior, gather production feedback, prioritize issues, and coordinate enhancements across engineering and product teams.
●Built RAG-powered applications using vector embeddings, PyTorch, OpenSearch, and enterprise data integrations, with focus on retrieval quality, troubleshooting, and production readiness.
●Supported production deployments from AI pilot to enterprise launch, managing Kubernetes-based environments, deployment validation, application monitoring, troubleshooting, and continuous reliability optimization.
●Led technical architecture for AI-native B2B SaaS platforms, building hands-on solutions with backend APIs, microservices, LLM orchestration, agentic AI workflows, RAG pipelines, and enterprise integrations.
●Collaborated with cross-functional engineering, data science, product, customer, and operations teams to resolve technical challenges, improve system scalability, performance, and reliability, and deliver production-grade solutions aligned with business requirements.
●Built background processing infrastructure using Celery workers and AWS services, separating long-running workloads from synchronous API requests.
●Designed cloud infrastructure across AWS, Kubernetes, Docker, S3, ECS, and related managed services for production AI applications.
●Developed ML inference services with FastAPI REST APIs, integrating trained models into distributed production systems.
●Built end-to-end ML pipelines covering EDA, feature engineering, model training, inference, deployment, monitoring, and drift detection.
●Implemented automated model monitoring and retraining workflows using Jenkins, Scikit-learn, Pandas, and performance thresholds.
●Designed enterprise data architectures spanning Oracle, MongoDB, Azure Cosmos DB, Azure SQL, and cloud services, with emphasis on scalability, security, and reliability.
●Worked directly with enterprise customers and product teams to identify system requirements, prototype solutions, and transition AI applications from POC to production.
●Led architecture and engineering decisions for enterprise AI systems while remaining hands-on across Python, TypeScript, APIs, cloud infrastructure, and ML/LLM components.
●Designed HIPAA-compliant data architecture across Oracle, Azure Cosmos DB, MongoDB, and Azure SQL; enforced PHI/PII protections with immutable audit logs and encryption at rest and in transit.
BairesDev, Remote - Senior Software Engineer
Apr 2020 - Jul 2023
●Built and enhanced a Python backend server, implementing robust APIs and scalable architecture to support real-time AI-powered features.
●Built and modernized cloud-native SaaS applications using Python backend services, React/TypeScript frontends, REST APIs, microservices, and AWS infrastructure.
●Developed scalable AI-enabled application features by integrating OpenAI, Anthropic, and Azure AI services into enterprise workflows.
●Delivered full-stack solutions across healthcare, enterprise portals, and customer-facing platforms using Node.js, JavaScript frameworks, databases, and cloud technologies.
●Collaborated with distributed engineering teams using Agile methodologies, participating in sprint planning, architecture discussions, code reviews, and production delivery.
●Developed full-stack enterprise applications using React, JavaScript, TypeScript, Node.js, and modern frontend engineering practices.
●Collaborated with distributed engineering teams to deliver AI-enabled products through Agile development, continuous iteration, and enterprise software practices.
●Managed end-to-end delivery from requirements and architecture through deployment, issue resolution, production support, and post-launch improvements.
●Managed end-to-end software delivery from requirements gathering, system architecture, API design, development, testing, deployment, production support, and post-launch optimization for enterprise applications.
●Worked as an embedded Senior Software Engineer within client engineering teams, contributing to Agile development, daily standups, sprint planning, technical troubleshooting, code reviews, and production issue resolution.
●Led a distributed engineering team of 15 developers, coordinating technical execution, architecture decisions, delivery planning, blocker resolution, and cross-functional collaboration with product owners.
●Designed and developed scalable backend architectures, REST APIs, microservices, and enterprise integrations supporting AI-powered applications and high-volume business workflows.
●Integrated OpenAI, Anthropic Claude, and Azure AI/LLM services into production systems, implementing LLM API integration, prompt engineering, AI orchestration, and intelligent workflow automation.
●Delivered software increments through Agile/Scrum sprint cycles, consistently meeting project milestones while adapting solutions to evolving business requirements and customer feedback.
●Supported cloud-native application development, SaaS modernization, AWS deployments, CI/CD pipelines, and production reliability improvements with focus on scalability, availability, security, and maintainability.
●Enabled the client to secure a five-year reseller agreement with one of the largest credit card issuing platforms in the market—a direct outcome of the successful SaaS transformation.
Deloitte, Atlanta, Georgia - Consultant
May 2016 - Mar 2020
●Performed exploratory data analysis (EDA) using Python (Pandas, NumPy, Matplotlib, Seaborn) to identify patterns, correlations, and anomalies.
●Developed enterprise healthcare and data platforms using React, Java Spring Boot, Node.js, Python, Flask, and REST APIs supporting large-scale business workflows.
●Built healthcare data processing solutions integrating EHR records, patient information, NLP-based document processing, and secure database architectures.
●Designed distributed backend services using Java 17, Spring Boot, Kafka, SQL databases, and cloud infrastructure for enterprise applications.
●Improved frontend performance and accessibility by developing React-based enterprise applications with reusable components, testing practices, and Agile delivery processes.
●Implemented event-driven architectures using Kafka, microservices, and distributed system patterns to improve scalability and system performance.
●Worked with secure healthcare data platforms involving HIPAA-compliant architectures, PII protection, encrypted storage, data privacy, and controlled access systems.
●Developed high-performance backend services using Node.js, FastAPI, Java, and Spring Boot, optimizing scalability and production response times.
●Automated infrastructure provisioning and deployment using Terraform, Docker, Jenkins, GitHub Actions, and CI/CD pipelines.
●Deployed AI/ML production services as scalable REST APIs using Flask and FastAPI, integrating real-time model inference into enterprise applications and distributed systems.
●Built and maintained cloud-native backend workflows using AWS services including S3, Lambda, Redshift, EKS, and RDS, supporting scalable data processing and production workloads.
●Supported high-availability production systems, troubleshooting backend performance issues, service failures, API integrations, and distributed system bottlenecks.
●Collaborated in Agile enterprise environments, managing software releases, technical improvements, incident resolution, and cross-functional engineering communication.
●Designed and developed healthcare data pipelines and HIPAA-compliant applications involving EHR data processing, Azure SQL, secure document storage, REST APIs, and NLP-based clinical data analysis.
●Delivered healthcare and life sciences technology solutions, providing hands-on experience with regulated data environments, clinical workflows, and enterprise AI applications.
●Managed scalable infrastructure with EKS, EC2, and RDS using Terraform automation, delivering fault-tolerant production environments for machine learning workloads.
Deloitte, Atlanta Metropolitan Area - Technology Analyst
May 2015 - May 2016
●Developed 15+ React, HTML, CSS, JavaScript UIs for a large-scale enterprise application with 300K+ monthly users, enhancing performance and achieving 95% WCAG accessibility compliance within an Agile environment.
●Mentored 4+ intern developers, trained in React.js and Redux, and led code reviews ensuring adherence to best practices.
●Enhanced product reliability by implementing unit and integration testing using Jest, achieving 95% code coverage and reducing production bug reports by 40%.
●Engineered Node.js middleware and REST API layers to streamline data flow between React components and enterprise microservices.
●Contributed to CI/CD automation by integrating GitHub Actions, Docker, and Git, improving release efficiency.
Deloitte, Atlanta Metropolitan Area - Software Engineering Intern
Jan 2015 - May 2015
●Synthesized customer research, market analysis, and design-thinking insights to develop acquisition recommendations for stakeholders
●Built ETL pipelines using Pandas to extract patient vitals and EHR records from multiple clinic systems into Azure SQL; processed unstructured consultation notes with NLP (text extraction, summarization), reducing documentation time by 20%.
●Developed Flask REST APIs for telehealth platform (patient registration, appointments, virtual consultations); implemented Redis caching reducing DB queries by 35%; achieved 75%+ pytest coverage across all endpoints.
●Designed HIPAA-compliant MySQL schema with encryption and Azure Blob Storage for secure medical document storage; implemented data retention policies with automated archiving.
Odesk & Upwork, Remote - Freelance Full-Stack Developer
Jan 2013 - May 2015
●Engineered MEAN stack applications including admin dashboards and interactive forms hosted on Heroku and AWS EC2.
●Developed WordPress sites and Laravel-based CMS tools with MySQL performance tuning.
●Assembled responsive frontends using HTML/CSS/JavaScript and Bootstrap; ensured cross-browser compatibility.
●Streamlined data parsing and reporting using Python scripts; maintained Java file processors and configured CI via Git and Jenkins.
RECENT AI PROJECT
Enterprise Knowledge Assistant
●Designed and developed an AI-powered knowledge assistant using OpenAI APIs, Retrieval-Augmented Generation (RAG), and vector embeddings to enable conversational search across enterprise documentation.
●Built document ingestion pipelines with semantic chunking, embedding generation, and vector indexing to improve retrieval quality.
●Implemented REST APIs integrating LLM responses into existing web applications while optimizing latency, token usage, and prompt quality.
●Collaborated on prompt engineering, evaluation, and user feedback loops to improve answer relevance and overall user experience.
EDUCATION
Georgia Institute of Technology - B.S. Computer Science
Aug 2011 - May 2015
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