Senior Software Cloud Fullstack Developer (Self ...

Job Title: Staff AI/ML full Stack Engineer & Lead (1 yr-Contract) Location: Normal, IL, Remote Employment Type: Full-time Role Summary We are seeking a Staff AI/ML solution lead to lead the architecture, design, and delivery of high-performance, enterprise-grade applications. This role combines deep hands-on coding with high-level architectural decision-making. You will work across frontend, backend, cloud infrastructure, database selection and integration layers, ensuring our systems are secure, scalable, and maintainable while enabling long-term technical growth. This hybrid role combines hands-on software engineering, devops and architectural leadership, enabling the delivery of robust, scalable, and innovative AI systems. Key Responsibilities: Architecture Leadership - Define system architecture, integration patterns, and technology standards for large-scale web and enterprise applications. Full Stack Development - Build and maintain robust, responsive applications using modern frontend frameworks (React, Vue, streamlit or Angular) and backend services in Python, Golang or RUST. Cloud & Infrastructure - Architect cloud-native solutions leveraging AWS with a focus on scalability, security, and performance. Implement containerized services with Docker and orchestrate deployments using Kubernetes (K8s). API & Service Design - Develop RESTful and GraphQL APIs for internal and external integrations. DevOps & CI/CD - Establish best practices for deployment pipelines, automated testing, and infrastructure-as-code (Terraform, Pulumi). Performance Optimization - Drive system performance tuning, load balancing, and efficient code design. Technical Mentorship - Coach and mentor engineers, conduct design/code reviews, and uphold engineering best practices. Cross-Functional Collaboration - Partner with product, design, and business teams to deliver impactful solutions aligned with company objectives. Databases: Will be performing database selection and deployment (strong devops experience required) ML: Experience with both ML and LLM stack design (model hubs, vector DBs, embedding pipelines). The role required knowledge to deploy end-to-end architecture of ML applications, traditional and RAG applications, Design of the MLOPS architectures databricks, aws and google ML ops: Strong uderstanding of Agentic AI, framework, best practices Clouds: Databricks, AWS mandatory End to End production level AI/MLl product deployment experience is required Qualifications Must Have: Required Qualifications: At least bachelor's in Computer Science mandatory 10+ years in deployment enterprise grade cloud level experience and 5+ years in software development 5+ years of experience with Databricks and AWS MLops deployment This role is more of a software lead and developer with strong Cloud experience to develop infra softwares. Architect end-to-end agentic pipelines and tools for others to contribute in the team The role required knowledge to deploy end-to-end architecture of ML applications, traditional and RAG applications. Architect end-to-end AI/ML systems from data ingestion to model deployment. Define best practices for model serving, data pipelines, and ML-OPS strategies. engineering, including hands-on model development and architectural design. Expertise in traditional ML, deep learning, LLMs, embeddings, and RAG frameworks. Strong software engineering skills: Python, API development, microservices, database design, and version control (Git). Experience with cloud platforms (AWS, Databricks, Google) and containerized deployments (Docker, Kubernetes). Knowledge of ML-OPS, CI/CD for AI, and production model monitoring. Strong understanding of software architecture patterns, distributed systems, and scalable data pipelines. Databases: Will be performing database selection and deployment (strong devops experience required) Preferred: Experience with event-driven architectures and messaging systems (NATs, Kafka, RabbitMQ). Familiarity with authentication and authorization frameworks (OAuth2, JWT, SSO). Knowledge of observability and monitoring tools (Prometheus, Grafana, OpenTelemetry). Background in designing large-scale enterprise or SaaS platforms. Python, Golang and Rust development experience is preferred Experience in manufacturing and predictive maintenance is a plus Background in controls engineering is a plus Soft Skills Strong decision-making and problem-solving skills in high-stakes technical environments. Ability to lead and influence architectural direction across teams. Excellent communication with both technical and non-technical stakeholders. Job Title: Staff AI/ML full Stack Engineer & Lead (1 yr-Contract) Location: Normal, IL, Remote Employment Type: Full-time Role Summary We are seeking a Staff AI/ML solution lead to lead the architecture, design, and delivery of high-performance, enterprise-grade applications. This role combines deep hands-on coding with high-level architectural decision-making. You will work across frontend, backend, cloud infrastructure, database selection and integration layers, ensuring our systems are secure, scalable, and maintainable while enabling long-term technical growth. This hybrid role combines hands-on software engineering, devops and architectural leadership, enabling the delivery of robust, scalable, and innovative AI systems. Key Responsibilities: Architecture Leadership - Define system architecture, integration patterns, and technology standards for large-scale web and enterprise applications. Full Stack Development - Build and maintain robust, responsive applications using modern frontend frameworks (React, Vue, streamlit or Angular) and backend services in Python, Golang or RUST. Cloud & Infrastructure - Architect cloud-native solutions leveraging AWS with a focus on scalability, security, and performance. Implement containerized services with Docker and orchestrate deployments using Kubernetes (K8s). API & Service Design - Develop RESTful and GraphQL APIs for internal and external integrations. DevOps & CI/CD - Establish best practices for deployment pipelines, automated testing, and infrastructure-as-code (Terraform, Pulumi). Performance Optimization - Drive system performance tuning, load balancing, and efficient code design. Technical Mentorship - Coach and mentor engineers, conduct design/code reviews, and uphold engineering best practices. Cross-Functional Collaboration - Partner with product, design, and business teams to deliver impactful solutions aligned with company objectives. Databases: Will be performing database selection and deployment (strong devops experience required) ML: Experience with both ML and LLM stack design (model hubs, vector DBs, embedding pipelines). The role required knowledge to deploy end-to-end architecture of ML applications, traditional and RAG applications, Design of the MLOPS architectures databricks, aws and google ML ops: Strong uderstanding of Agentic AI, framework, best practices Clouds: Databricks, AWS mandatory End to End production level AI/MLl product deployment experience is required Qualifications Must Have: Required Qualifications: At least bachelor's in Computer Science mandatory 10+ years in deployment enterprise grade cloud level experience and 5+ years in software development 5+ years of experience with Databricks and AWS MLops deployment This role is more of a software lead and developer with strong Cloud experience to develop infra softwares. Architect end-to-end agentic pipelines and tools for others to contribute in the team The role required knowledge to deploy end-to-end architecture of ML applications, traditional and RAG applications. Architect end-to-end AI/ML systems from data ingestion to model deployment. Define best practices for model serving, data pipelines, and ML-OPS strategies. engineering, including hands-on model development and architectural design. Expertise in traditional ML, deep learning, LLMs, embeddings, and RAG frameworks. Strong software engineering skills: Python, API development, microservices, database design, and version control (Git). Experience with cloud platforms (AWS, Databricks, Google) and containerized deployments (Docker, Kubernetes). Knowledge of ML-OPS, CI/CD for AI, and production model monitoring. Strong understanding of software architecture patterns, distributed systems, and scalable data pipelines. Databases: Will be performing database selection and deployment (strong devops experience required) Preferred: Experience with event-driven architectures and messaging systems (NATs, Kafka, RabbitMQ). Familiarity with authentication and authorization frameworks (OAuth2, JWT, SSO). Knowledge of observability and monitoring tools (Prometheus, Grafana, OpenTelemetry). Background in designing large-scale enterprise or SaaS platforms. Python, Golang and Rust development experience is preferred Experience in manufacturing and predictive maintenance is a plus Background in controls engineering is a plus Soft Skills Strong decision-making and problem-solving skills in high-stakes technical environments. Ability to lead and influence architectural direction across teams. Excellent communication with both technical and non-technical stakeholders. ['Agentic Framework', 'AI architecture development', 'AWS', 'Databricks', 'End to End to AI project lead', 'Production level project deployment'] Shift: ['Agentic Framework', 'AI architecture development', 'AWS', 'Databricks', 'End to End to AI project lead', 'Production level project deployment']

Created: 2026-03-10