Senior Software Cloud Fullstack Developer; Self Driving

Senior Software Cloud Fullstack Developer (Self Driving)

• Normal, IL

Job #: 3829

Category: Manufacturing

Job Title: Staff AI/ML Full-Stack Engineer & Technical Lead (Contract ? 1 Year)

Location: Remote (Normal, IL)

Employment Type: Full-Time

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.

• 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 Graph
  
  QL 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

• 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 Dev Ops 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

• 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

• 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

• 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 Dev Ops practices

• Experience with event‑driven architectures and messaging systems (Kafka, Rabbit
  
  MQ, NATS)
• Familiarity with authentication/authorization (OAuth2, JWT, SSO)
• Knowledge of observability tools (Prometheus, Grafana, Open Telemetry)
• Experience building large‑scale enterprise or SaaS platforms
• Proficiency in Python, Golang, or Rust
• Experience in manufacturing, predictive maintenance, or controls engineering

• 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