Senior Software Cloud Fullstack Developer (Self Driving)

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 

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