What are the responsibilities and job description for the Senior AI SDK & Scaffolding Engineer position at Purple Drive?
Dear Supplier Partners,
Looking For Senior AI SDK & Scaffolding Engineer For Our Client
Location:- Oaks, PA
Role Name - Senior AI SDK & Scaffolding Engineer
Skills: AI Agents~AI & Gen AI - Products & Tools
Experience Required: 10 & Above
Role Descriptions:
The Senior AI SDK and Scaffolding Engineer will build the reusable engineering framework and developer toolkit that enables teams to rapidly create standardized enterprise AI solutions without rebuilding common components for every project.
Key Responsibilities
• SDK Development: Design, build, and maintain client-facing AI SDKs in languages like TypeScript, Python, or Go to interact with backend LLM services and agent frameworks.
• Scaffolding & Boilerplate Tools: Create command-line interfaces (CLIs) and project starter templates that let engineers spin up production-ready AI applications in minutes.
• API & Interface Design: Establish clean, intuitive, and well-documented APIs for internal or external developers consuming AI capabilities.
• Agent & Workflow Integration: Embed support for modern LLM orchestrators (such as LangChain, LlamaIndex, or native model APIs) directly into the developer scaffolding.
• Testing & Reliability: Implement rigorous automated testing, validation mechanisms, and mocking tools for AI SDK components to prevent regressions.
• Documentation & Evangelism: Write comprehensive developer documentation, quickstart guides, and code examples to drive adoption.
• Design and build reusable SDKs, libraries, frameworks, templates, and reference implementations for AI development.
• Develop project scaffolding for common AI solution patterns.
• Create reusable components for model invocation, prompt management, RAG, agent orchestration, logging, security, and evaluation.
• Build standardized interfaces that allow applications to work with multiple AI models/providers where appropriate.
• Develop reusable patterns for token management, caching, model routing, retries, error handling, and observability.
• Create developer tooling and automation to accelerate AI application delivery.
• Embed enterprise security and governance requirements into reusable frameworks.
• Establish coding standards, testing frameworks, package-management approaches, and version-management practices.
• Develop documentation, examples, starter applications, and engineering guidance.
• Partner with AI architects and platform engineers to create an integrated AI engineering harness.
• Support development teams adopting the SDK and gather feedback to continuously improve the framework.
Required Skills
• Strong software engineering experience with Python and/or modern enterprise programming languages.
• Deep understanding of software framework and SDK design.
• Experience with APIs, microservices, reusable libraries, automated testing, CI/CD, and developer tooling.
• Hands-on GenAI engineering experience.
• Familiarity with LLM APIs, RAG, agents, embeddings, model orchestration, and evaluation frameworks.
• Strong understanding of software-design principles and enterprise engineering standards.
Preferred Experience
• 8 years of software engineering experience.
• Experience developing internal developer platforms, SDKs, frameworks, or reusable application foundations.
• Demonstrated experience converting AI prototypes into standardized, production-ready capabilities.