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Metro location, mid-level (3+ years), broad fullstack skillset, and a strong brand increase applicant competition.
Full-stack, cloud and API skills with some AI exposure are broadly transferable across industries.
Explicit 3+ years plus multiple required cloud, microservices, and AI/tool proficiencies implies moderate filtering.
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Design, build, and implement AI agents and copilots using frameworks like Retrieval Augmented Generation (RAG) to enhance enterprise platforms.
Develop and maintain secure, scalable full-stack applications integrating AI models via RESTful or GraphQL APIs with frontend and backend technologies.
Deploy, monitor, and optimize AI-driven applications using containerization (Docker/Kubernetes) and cloud services (Azure); validate integrations between supply chain, planning, finance, and other systems.
Bachelor’s degree in Computer Science, Engineering, or related field (or suitable combination of education/experience).
3+ years of professional software engineering experience building and operating production systems.
Proficiency in microservices architecture, domain driven design, RESTful APIs; programming in Python, TypeScript/JavaScript, Java/Kotlin, or Go.
Experience with cloud services (AWS or Azure), container orchestration (Docker/Kubernetes), and CI/CD pipelines.
Experienced full-stack engineer with strong coding fundamentals and a quality-first mindset in highly collaborative, multidisciplinary teams.
Hands-on experience or strong interest in AI technologies including Large Language Models, AI agents, and AI-assisted development/testing tools.
Capable of designing and debugging AI agent behaviors, prompt engineering, and integrating AI-driven automation in enterprise environments.