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Medium—known services firm and popular AI engineering role with broad technical requirements.
Medium—ML, cloud, and microservices skills transfer across industries, but telemetry and enterprise-specific expertise raises domain fit needs.
High—many mandatory technical competencies across cloud, ML, microservices, containers, and CI/CD.
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Design, develop, and test software systems/modules including cloud-based and AI/ML data processing tools in a micro-services environment.
Accountable for writing, testing, refactoring code and automated testing, contributing to deployment and integration across multiple teams.
Prototype multi-vendor infrastructure solutions and present internally and to clients, working with APIs and telemetry data handling structured and unstructured data.
Bachelor's degree in Computer Science, Engineering or related field.
Seasoned experience in software development including micro-services, RESTful APIs, and AI/ML algorithms on large datasets.
Strong expertise with cloud architectures (AWS, GCP, Azure), container runtimes (Kubernetes, Docker), multiple programming languages (C/C++, Java, Python, etc.), and CI/CD practices.
Work Experience Required: Seasoned experience working with geo-distributed teams, Agile/Lean methodologies, and full software delivery lifecycle tools.
Experienced in building large scale distributed systems with microservices and API product development across multiple public clouds.
Thrives in dynamic, fast-paced environments with cross-functional and geo-distributed teams, demonstrating strong debugging and analytical skills.
Operates with a deep technical subject matter expertise in cloud infrastructure, data stores (SQL and NoSQL), automation, and test-driven development approaches.