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

Were 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

• Bachelors 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