Senior Software Cloud Fullstack Developer (Self Driving)
Premier Staffing Solution, Normal, IL, United States
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
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