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