AI Application Platform Engineer

AI Application Platform Engineer
Senior Individual Contributor | Full Stack | Generative AI | Agentic Development | Azure
Fully Remote Contract Position | 1099 | 80-95 USD/hr
Position Summary
Osborn & Holloway is seeking a senior AI Application Platform Engineer to help design and build an internal application incubation platform that fundamentally changes how business applications are conceived and developed.
The objective is ambitious: create a secure, governed, prompt-driven environment that allows technically curious business users to design and build custom web applications without requiring them to become professional software developers or understand the underlying complexity of enterprise software development.
A business user should be able to describe the problem they are trying to solve, refine requirements conversationally, and progressively create a functioning application. Behind that simple experience, the platform must translate business intent into appropriate application architecture, data structures, user experiences, application code, tests, documentation, and deployment artifacts.
We are not trying to eliminate SDLC. We are trying to encode SDLC into the platform so the business user does not have to perform it manually.
This role will work closely with a complementary Azure Application Platform & DevSecOps Engineer. Together, these engineers will design and build a “system that builds systems.”
What Makes This Role Different
We are specifically looking for an experienced software engineer who has embraced AI-assisted development and emerging “vibe coding” techniques without abandoning the engineering principles that make enterprise software secure, maintainable, testable, and supportable.
The successful candidate will understand traditional software engineering well enough to determine which parts of the development lifecycle can safely be automated, abstracted, or delegated to AI—and which cannot.
This is not a traditional application-development position, nor is it simply a prompt-engineering role. The successful candidate will help create the platform, agents, reusable patterns, controls, and abstractions that enable other people to build applications safely.
Key Responsibilities AI-Assisted Application Engineering
· Design and develop the prompt-driven application-building experience used by non-technical and semi-technical business users.
· Translate natural-language business intent into structured requirements, application specifications, data models, user experiences, and implementation artifacts.
· Develop agentic workflows capable of gathering requirements, identifying ambiguity, asking appropriate follow-up questions, and progressively refining application designs.
· Integrate Azure-hosted generative AI and LLM capabilities into application-development workflows.
· Develop structured prompting, context-management, tool-calling, validation, and orchestration patterns.
· Evaluate and incorporate emerging AI-assisted coding techniques and development tools where they provide meaningful value.
· Establish mechanisms for validating AI-generated code before it can progress through the application lifecycle.
Full-Stack Application Development
· Design and develop modern web applications using appropriate JavaScript/TypeScript frameworks and supporting technologies.
· Develop reusable front-end components, APIs, services, templates, application shells, and architectural patterns.
· Design practical relational and non-relational data structures appropriate to generated applications.
· Build reusable application capabilities for authentication, authorization, configuration, logging, error handling, notifications, and other common enterprise requirements.
· Create application scaffolding that allows generated solutions to begin from approved architectural patterns rather than unrestricted blank-slate code generation.
· Ensure generated applications remain understandable, maintainable, testable, and transferable to professional engineering teams when required.
Business-to-Application Translation
· Help design conversational experiences that allow business users to describe problems in their own language rather than in software-development terminology.
· Build mechanisms for converting business requirements into structured development artifacts.
· Incorporate business-analysis concepts into the application-generation process, including requirements clarification, use cases, acceptance criteria, process flows, and data requirements.
· Identify when a user’s requested solution has evolved beyond the boundaries appropriate for citizen development.
· Design escalation or “graduation” mechanisms that transition complex or high-risk applications into formal engineering and governance processes.
Automated Quality and SDLC
· Build automated testing and validation into the generation process.
· Integrate generated applications with Git-based source control and Azure DevOps.
· Support automated generation of documentation, work items, test cases, release artifacts, and other SDLC assets.
· Collaborate on mechanisms that ensure applications follow established DEV, test/UAT, and production promotion paths.
· Design for traceability between user intent, requirements, generated code, testing, and deployed functionality.
Platform Development
· Work closely with the Azure Application Platform & DevSecOps Engineer to integrate application generation with automated Azure provisioning.
· Define clear interfaces between the AI/application-generation layer and the underlying infrastructure/governance layer.
· Participate in architectural decisions governing the overall incubation platform.
· Help establish reusable standards that allow the platform to support progressively broader application use cases.
Required Qualifications
· Significant professional full-stack software-development experience.
· Strong experience with modern web application development and API design.
· Strong JavaScript and/or TypeScript experience and familiarity with modern front-end frameworks such as React.
· Practical experience using generative AI and AI-assisted software-development tools.
· Demonstrable understanding of LLM capabilities, limitations, context management, structured prompting, and tool/function calling.
· Strong understanding of application architecture, data modeling, APIs, authentication, authorization, testing, and software-design principles.
· Experience with Git-based source control and modern CI/CD practices.
· Working knowledge of Microsoft Azure.
· Practical understanding of Agile software-development methodologies.
· Ability to translate ambiguous business problems into structured technical solutions.
· Strong written and verbal English communication skills.
· Ability to work independently while collaborating closely with another senior engineer across overlapping areas of responsibility.
Preferred Qualifications
· Experience with Azure OpenAI or comparable enterprise generative-AI platforms.
· Experience designing agentic applications or multi-agent workflows.
· Experience with Microsoft Power Platform, Power Automate, Dataverse, or related low-code technologies.
· Experience with Azure DevOps.

Work arrangement
Yes