Senior Software Cloud Fullstack Developer (Self Driving)

Senior Software Cloud Fullstack Developer (Self Driving) Normal, IL Job ID#: 3829 Category: Manufacturing Position Type Contractor (W-2) Job Description Job Title: Staff AI/ML Full-Stack Engineer & Technical Lead (Contract ? 1 Year) Location: Remote (Normal, IL) Employment Type: Full-Time Overview We're hiring a Staff AI/ML Engineer & Technical Lead to own the architecture and delivery of scalable, enterprise-grade AI applications. This is a hands-on leadership role spanning full-stack development, cloud infrastructure, and end-to-end ML system design. Responsibilities Lead system architecture, technology selection, and integration design Build and scale full-stack applications (React/Vue/Streamlit/Angular + Python/Golang/Rust) Design and deploy cloud-native systems on AWS using Docker and Kubernetes Develop REST and GraphQL APIs for internal and external use Implement CI/CD pipelines, automated testing, and IaC (Terraform, Pulumi) Optimize performance, scalability, and reliability across systems Mentor engineers and enforce best practices through code/design reviews Partner with product and business teams to deliver impactful solutions Requirements Strong experience in full-stack engineering and system architecture Deep knowledge of AWS and Databricks (required); GCP is a plus Expertise in database selection, deployment, and DevOps practices Hands-on experience with ML and LLM systems (RAG, vector DBs, embeddings) Solid understanding of MLOps, including deployment and monitoring pipelines Experience building and deploying production-grade AI/ML applications end-to-end Job Requirements Required Qualifications Bachelor's degree in Computer Science (required) 10+ years of enterprise cloud deployment experience; 5+ years in software development 5+ years of hands-on experience with AWS and Databricks in MLOps environments Strong background as a hands-on software lead building cloud infrastructure and platforms Core Expertise Architect and deploy end-to-end AI/ML systems, including traditional ML and RAG-based applications Design agentic AI pipelines and reusable frameworks for team-wide contribution Define best practices for model serving, data pipelines, and MLOps strategies Hands-on experience with model development and system architecture Technical Skills Expertise in ML, deep learning, LLMs, embeddings, and RAG frameworks Strong software engineering skills: Python, APIs, microservices, database design, Git Experience with AWS, Databricks (required), and GCP (preferred) Proficiency in containerization and orchestration (Docker, Kubernetes) Solid understanding of MLOps, CI/CD for AI, and production monitoring Experience with distributed systems, scalable architectures, and data pipelines Database selection, deployment, and optimization with strong DevOps practices Preferred Qualifications Experience with event-driven architectures and messaging systems (Kafka, RabbitMQ, NATS) Familiarity with authentication/authorization (OAuth2, JWT, SSO) Knowledge of observability tools (Prometheus, Grafana, OpenTelemetry) Experience building large-scale enterprise or SaaS platforms Proficiency in Python, Golang, or Rust Experience in manufacturing, predictive maintenance, or controls engineering Soft Skills Strong problem-solving and decision-making in complex technical environments Ability to lead architectural direction and influence across teams Clear communication with both technical and non-technical stakeholders J-18808-Ljbffr