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