Staff AI/ML Full Stack Lead Engineer

As a Staff AI/ML Full Stack Lead Engineer, you will play a crucial role in leading the architecture, design, and delivery of high-performance, enterprise-grade applications. Your responsibilities will include: - 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. Your qualifications must include: - Must Have: - Bachelors in Computer Science - 10+ years of deployment enterprise-grade cloud-level experience and 5+ years in software development - 5+ years of experience with Databricks and AWS MLops deployment - Strong understanding of Agentic AI, ML-OPS, and Cloud platforms (Databricks, AWS) - 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 Your role will require you to work on CST Time zone and possess strong decision-making, problem-solving skills, and excellent communication abilities with both technical and non-technical stakeholders. As a Staff AI/ML Full Stack Lead Engineer, you will play a crucial role in leading the architecture, design, and delivery of high-performance, enterprise-grade applications. Your responsibilities will include: - 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. Your qualifications must include: - Must Have: - Bachelors in Computer Science - 10+ years of deployment enterprise-grade cloud-level experience and 5+ years in software development - 5+ years of experience with Databricks and AWS MLops deployment - Strong understanding of Agentic AI, ML-OPS, and Cloud platforms (Databricks, AWS) - 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 Your role will require you to work on CST Time zone and possess strong decision-making, problem-solving skills, and excellent communication abilities with both technical and non-technical stakeholders.