Develop and implement secure, end-to-end cluster and application lifecycles in cloud environments, focusing on DevSecOps practices and space mission support.
Compensation
Basic Compensation: $120,000 - $150,000 (For Colorado Springs, CO Only)
Responsibilities
Develop and implement secure, end-to-end cluster and application lifecycles in cloud environments
Collaborate with clients and internal teams to design and implement containerization solutions using Kubernetes or Docker
Build and maintain CI/CD pipelines, ensuring a smooth, secure software update process
Apply GitOps principles for software delivery automation
Support the organization’s goals of enhancing security, scalability, and operational efficiency
Requirements
Bachelor's degree in Computer Science or related field
Design and implement product features in collaboration with developers, architects, product owners, and domain experts. Develop production-grade Python code for industrial IoT and timeseries data analytics applications. Build scalable data-processing algorithms using machine-learning-based and deterministic approaches. Develop backend services, web applications, and REST APIs using FastAPI or Flask. Design and maintain efficient data pipelines and ETL processes for large-scale timeseries datasets. Write unit, integration, and component test cases following software engineering best practices. Deploy and operationalize solutions on Microsoft Azure, including Azure Functions and Azure Databricks. Investigate and resolve production issues, incorporate stakeholder feedback, and drive continuous improvements.
Responsibilities
Design and implement product features in collaboration with developers, architects, product owners, and domain experts.
Develop production-grade Python code for industrial IoT and timeseries data analytics applications.
Build scalable data-processing algorithms using machine-learning-based and deterministic approaches.
Develop backend services, web applications, and REST APIs using FastAPI or Flask.
Design and maintain efficient data pipelines and ETL processes for large-scale timeseries datasets.
Requirements
Bachelor’s or master’s degree in Computer Science, Electronics and Communication, Electrical Engineering, Data Engineering, or equivalent.
Lead and mentor an engineering team focused on architecting and delivering AI-powered conversational platforms.
Responsibilities
Architect, build, and deploy enterprise-grade digital and voice assistants, chatbots, and AI agent platforms at scale
Oversee multi-step AI workflow orchestration, tool/function calling, state management, and RAG pipelines integrated with complex enterprise backends
Drive quality assurance, performance optimization, model evaluation, safety guardrails, and compliance across all conversational touchpoints
Lead a team of small-to-medium AI Conversational Engineers, providing technical guidance, career development, mentorship, and continuous growth opportunities
Establish engineering best practices, standards, and testing methodologies
Senior-level engineering role focused on developing, designing, and maintaining application software and services, leading code reviews, and mentoring junior engineers within the OCI environment.
Compensation
US: Hiring Range in USD from: $86,100 to $187,000 per annum. May be eligible for bonus and equity.
Responsibilities
Adheres to and suggests improvements to all phases of the application software development lifecycle
Develops new application features and enhancements following design specifications
Leads code reviews in designated application areas to help drive improvements
Conducts debugging and troubleshooting to identify and fix moderately complex application issues
Troubleshoots and resolves moderately complex issues related to API functionality, integration, and service-to-service interactions
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