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Job Title: AI Platform Engineer II
Location: Memphis, TN preferred. Remote candidates may be considered if qualified local candidates are not identified.
Overview
We are seeking an experienced AI Platform Engineer II to help build, automate, deploy, and support production AI applications and platform capabilities.
This is an engineering-first AI role. The strongest candidates will bring a solid background in software engineering, backend engineering, platform engineering, or cloud engineering, along with either hands-on AI/GenAI experience or demonstrated ability to quickly learn and apply emerging AI technologies.
This role is not focused on simply knowing AI tools or frameworks. We are looking for an experienced engineer who can independently own meaningful technical work, operate effectively when requirements are not fully defined, identify and solve problems proactively, evaluate technical alternatives, and take solutions from design through production.
Candidates may lean more heavily toward AI application development or AI platform/cloud engineering. A perfectly balanced background across both areas is not required.
Key Responsibilities
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Design, build, enhance, deploy, and support production AI applications and platform capabilities.
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Develop backend services, APIs, integrations, scripts, automation, and supporting engineering tooling.
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Contribute to AI-powered applications, LLM-based services, Retrieval-Augmented Generation (RAG) solutions, AI workflows, and enterprise AI integrations.
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Build automation that improves platform scalability, reliability, manageability, monitoring, and operational efficiency.
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Integrate AI capabilities with enterprise applications, APIs, systems, and data sources.
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Own meaningful engineering work from requirements and design through implementation, deployment, monitoring, troubleshooting, and continued improvement.
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Develop and deploy applications and services using established CI/CD and cloud-native engineering practices.
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Work with containerized environments such as Docker and Kubernetes.
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Support production platforms through troubleshooting, monitoring, observability, and reliability improvements.
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Apply appropriate security, dependency management, vulnerability scanning, access control, logging, and governance practices.
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Work effectively through technical ambiguity and independently identify problems and improvement opportunities.
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Evaluate alternatives, propose solutions, and make sound engineering decisions.
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Collaborate with software, platform, product, data, security, and other technical teams.
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Participate in code reviews, technical discussions, Agile delivery, and production support.
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Provide technical guidance, code review, documentation, and knowledge sharing to less-experienced engineers.
Required Qualifications
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5–7+ years of professional experience in software engineering, backend engineering, platform engineering, cloud engineering, or a closely related field.
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Strong software or platform engineering fundamentals with demonstrated experience independently owning meaningful technical work.
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Proven ability to design, build, deploy, and support production-quality software or platform capabilities.
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Experience developing backend applications, services, APIs, automation, integrations, or cloud/platform solutions.
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Proficiency in at least one modern programming language such as Python, Java, or TypeScript.
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Experience working within mature engineering practices including source control, testing, CI/CD, deployment, monitoring, and production support.
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Demonstrated ability to work through ambiguity, independently solve technical problems, evaluate alternatives, and take ownership from problem identification through delivery.
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Experience with AI/GenAI solutions or a strong software/platform engineering background with demonstrated ability to quickly learn and apply new technologies.
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Strong problem-solving, collaboration, written communication, and verbal communication skills.
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Bachelor's degree in Computer Science, Software Engineering, Infrastructure Engineering, Cloud Engineering, or a related field, or equivalent professional experience.
Preferred Qualifications
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Experience building or integrating production AI/GenAI applications or services.
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Experience with LLM-based applications, AI-enabled backend services, or AI platform engineering.
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Retrieval-Augmented Generation (RAG), vector search, embeddings, metadata filtering, or retrieval engineering experience.
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Agentic AI or AI workflow automation experience.
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Experience with GenAI frameworks or platforms such as LangChain, LlamaIndex, Semantic Kernel, AWS Bedrock, Azure OpenAI, OpenAI, or comparable technologies.
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Python development or automation experience.
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Experience with AWS, Azure, or GCP.
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Docker and Kubernetes experience.
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Experience with CI/CD pipelines and cloud-native application development.
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API gateway or LLM gateway experience.
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Monitoring and observability experience.
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Enterprise security, governance, access control, or compliance experience.
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Experience mentoring, supporting, or enabling other engineers.
How to Apply
Qualified candidates are encouraged to submit a resume for confidential consideration. We are particularly interested in experienced engineers who can demonstrate technical ownership, strong engineering fundamentals, independent problem-solving, and the ability to become productive quickly in a modern AI engineering environment.