Senior Software Cloud Fullstack Developer (Self Driving)

Senior Software Cloud Fullstack Developer (Self Driving)Normal, ILJob ID#: 3829Category: ManufacturingPosition TypeContractor (W-2)Job DescriptionJob Title: Staff AI/ML Full-Stack Engineer & Technical Lead (Contract ? 1 Year)Location: Remote (Normal, IL)Employment Type: Full-TimeOverviewWe'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.ResponsibilitiesLead system architecture, technology selection, and integration designBuild and scale full‑stack applications (React/Vue/Streamlit/Angular + Python/Golang/Rust)Design and deploy cloud‑native systems on AWS using Docker and KubernetesDevelop REST and GraphQL APIs for internal and external useImplement CI/CD pipelines, automated testing, and IaC (Terraform, Pulumi)Optimize performance, scalability, and reliability across systemsMentor engineers and enforce best practices through code/design reviewsPartner with product and business teams to deliver impactful solutionsRequirementsStrong experience in full‑stack engineering and system architectureDeep knowledge of AWS and Databricks (required); GCP is a plusExpertise in database selection, deployment, and DevOps practicesHands‑on experience with ML and LLM systems (RAG, vector DBs, embeddings)Solid understanding of MLOps, including deployment and monitoring pipelinesExperience building and deploying production‑grade AI/ML applications end‑to‑endJob RequirementsRequired QualificationsBachelor's degree in Computer Science (required)10+ years of enterprise cloud deployment experience; 5+ years in software development5+ years of hands‑on experience with AWS and Databricks in MLOps environmentsStrong background as a hands‑on software lead building cloud infrastructure and platformsCore ExpertiseArchitect and deploy end‑to‑end AI/ML systems, including traditional ML and RAG‑based applicationsDesign agentic AI pipelines and reusable frameworks for team‑wide contributionDefine best practices for model serving, data pipelines, and MLOps strategiesHands‑on experience with model development and system architectureTechnical SkillsExpertise in ML, deep learning, LLMs, embeddings, and RAG frameworksStrong software engineering skills: Python, APIs, microservices, database design, GitExperience with AWS, Databricks (required), and GCP (preferred)Proficiency in containerization and orchestration (Docker, Kubernetes)Solid understanding of MLOps, CI/CD for AI, and production monitoringExperience with distributed systems, scalable architectures, and data pipelinesDatabase selection, deployment, and optimization with strong DevOps practicesPreferred QualificationsExperience 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 platformsProficiency in Python, Golang, or RustExperience in manufacturing, predictive maintenance, or controls engineeringSoft SkillsStrong problem‑solving and decision‑making in complex technical environmentsAbility to lead architectural direction and influence across teamsClear communication with both technical and non‑technical stakeholders#J-18808-Ljbffr