Senior GenAI SDK Engineer

Location: Oaks, PA
Experience Required: 10+ Years

Primary Skills

• AI Agents

• Generative AI (GenAI)

• AI SDK Development

• Python

• AI Frameworks and Scaffolding

Secondary Skills

• TypeScript and Go

• LLM APIs and Model Integration

• Retrieval-Augmented Generation (RAG)

• LangChain and LlamaIndex

• Agent Orchestration and Workflow Integration

• API and Microservices Development

• CLI Tools and Project Templates

• Prompt Management and Embeddings

• Automated Testing and CI/CD

• Developer Tooling and Automation

• Model Routing, Caching, and Token Management

• Logging, Monitoring, and Observability

• Enterprise Security and Governance

• Documentation and Technical Standards

Job Description

We are looking for a highly experienced Senior AI SDK & Scaffolding Engineer to build reusable engineering frameworks, developer toolkits, and standardized foundations that enable teams to develop enterprise-grade AI solutions efficiently.

The ideal candidate will have strong software engineering expertise, hands-on Generative AI experience, and a deep understanding of SDK design, developer tooling, and modern AI application architectures.

Key Responsibilities

• Design, develop, and maintain reusable AI SDKs and libraries using Python, TypeScript, Go, or other modern programming languages.

• Build command-line interfaces (CLIs), project scaffolding, boilerplate tools, and starter templates for production-ready AI applications.

• Design intuitive, well-documented APIs and reusable components for AI development.

• Integrate LLM orchestration frameworks, including LangChain, LlamaIndex, and native model APIs.

• Develop reusable components for model invocation, prompt management, RAG, agent orchestration, logging, security, and evaluation.

• Build standardized interfaces to support multiple AI models and providers.

• Implement token management, caching, model routing, retries, error handling, and observability.

• Establish automated testing, validation, CI/CD, package management, and version control practices.

• Embed enterprise security, governance, and engineering standards into reusable frameworks.

• Create technical documentation, quickstart guides, code examples, and reference implementations.

• Collaborate with AI architects, platform engineers, and development teams to improve AI engineering tools and frameworks.

• Gather developer feedback and continuously enhance SDK usability, reliability, and adoption.

Required Qualifications

• Strong software engineering experience with Python and/or other modern enterprise programming languages.

• Deep understanding of SDK development, software frameworks, and reusable libraries.

• Experience with APIs, microservices, automated testing, CI/CD, and developer tooling.

• Hands-on experience in Generative AI engineering.

• Familiarity with LLM APIs, RAG, AI agents, embeddings, model orchestration, and evaluation frameworks.

• Strong understanding of software design principles and enterprise engineering standards.