Software Engineer

Dylan Devera

608-***-**** ****************@*****.*** linkedin.com/in/dylan-devera-0808153a3/ github.com/frankomondo Nevada US PROFESSIONAL SUMMARY

Senior AI/ML Full-Stack Engineer & MLOps Architect specializing in production-grade, cloud-native ML pipelines in regulated environments. Architect end-to-end systems including recommendation engines, LLM-powered APIs, scalable GKE infrastructure, Airflow orchestration, and custom feature stores for seamless offline-to-real-time inference with strict compliance. Excel in cross-functional collaboration, mentoring, and rapid iteration, bridging domain experts and engineering teams to deliver high-impact AI solutions. Focused on 01 AI product development in stealth startups, with expertise in Rust/Python, microservices, scalable ML training/serving, and advancing healthcare AI through modern MLOps and LLM innovations.

EDUCATION

Argosy University September 2009 - July 2013

Computer Science Bachelor's Degree

EXPERIENCE

Senior Software Engineer

Chiral October 2025 - Present New York, NY

Architected and deployed LLM-powered text extraction APIs, achieving 99.8% uptime and processing over 50,000 documents daily. Engineered full-stack scalable AI services, supporting growth from 0 to 10 million monthly API requests within 6 months. Partnered with founders to iterate on core product features, accelerating impactful releases and product-market fit by delivering 5 major iterations 4 weeks ahead of schedule.

Drove performance and reliability in startup delivery cycles, leveraging agile leadership and rapid prototyping to reduce cycle time by 40%. Spearheaded cross-functional collaboration to resolve ambiguous requirements and resource constraints, accelerating blocker resolution by 3x (from ~9 days to ~3 days average).

Senior Software Engineer/Software Architect

GE Healthcare February 2019 - August 2025 Chicago, IL Led architecture and implementation of cloud-native ML pipelines for healthcare imaging and AI applications, enabling seamless data-to- inference workflows and reducing end-to-end latency by 50%. Designed and built graph-based recommendation systems and scalable GKE-based ML infrastructure for training and serving, improving model serving throughput by 60%.

Engineered automated ML workflows with Airflow, streamlining data ingestion, model training, and deployment to cut deployment time by 70%.

Built and refined a custom feature store, powering consistent data access for offline training and online prediction and decreasing feature retrieval latency by 45%.

Accelerated deployment of high-accuracy AI models by implementing MLOps best practices and fostering strong stakeholder relationships, shortening release cycles from months to days (75% faster). Software Engineer

Blacc Spot Media February 2015 - January 2019 Atlanta, GE Developed cloud communications platforms using WebRTC and programmable APIs for real-time client applications, supporting 10,000+ concurrent users with <100ms latency.

Architected microservices and optimized performance to deliver high-engagement features ahead of schedule, completing projects 3 weeks early on average.

Mentored junior engineers and led agile iterations in a fast-paced, results-driven consulting environment, boosting team velocity by 35%. Designed microservices architectures for real-time messaging and voice/video features, enabling the system to handle 5x traffic spikes without downtime and reducing peak latency by 60%. Collaborated with clients to deliver custom, high-performance digital solutions, improving reliability and efficiency by reducing system errors 50% and increasing uptime to 99.9%.

Software Engineer

University Hospitals September 2013 - February 2015 Shaker Heights, OH Developed backend services for healthcare data processing and integration, improving system uptime and reliability to 99.95% availability. Modernized legacy codebases and implemented robust testing to ensure regulatory compliance and secure solutions, cutting compliance- related incidents by 60%.

Collaborated with clinical stakeholders to translate requirements into scalable technical solutions, delivering 8 critical integrations 2 months ahead of timeline.

Implemented secure, compliant code practices to meet healthcare regulations and optimize system availability, reducing security vulnerabilities by 70%.

Troubleshot systems for high-availability in mission-critical clinical environments, minimizing downtime incidents by 80%. SKILLS

AI/ML & Data Science: Python, PyTorch, TensorFlow, Scikit-learn, LLMs (Fine-tuning & Prompt Engineering), NLP, Graph-based Recommendation Systems, Feature Engineering, Model Evaluation & Monitoring, Data structures Programming Languages: Rust, Python, C++, Java, TypeScript Frontend: React, Next.js, Angular, Vue, JavaScript/TypeScript, Html, Css Backend & Full-Stack: FastAPI, Flask, Django, Node.js, Express, Microservices, REST & GraphQL APIs, WebSockets, Web services, Distributed systems

MLOps & DevOps: Airflow, Kubeflow, MLflow, Docker, Kubernetes (GKE), CI/CD Pipelines, Model Deployment & Monitoring Cloud Platforms & Infrastructure: GCP (GKE), AWS SageMaker, AWS EC2, AWS ECS, Azure ML, Terraform, Cloud-Native Architecture Databases & Big Data: PostgreSQL, MongoDB, DynamoDB, MySql, Oracle, Redis, Cassandra, Apache Spark, Apache kafka, Vector Databases (Pinecone/Chroma), BigQuery

Healthcare & Regulated AI: HIPAA/FDA Compliance, Regulated Environment ML Production, Clinical AI Systems, Real-time Prediction Other Technologies: Creative problem-solving, Continuous learning, Confidence, Guidance, Documentation, Scheduling, Decision- making, Communication skills, Code reviews, Product management, Team collaboration, Teamwork, Proactive, Innovation, Fintech, Diversity and inclusion

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