York Solutions, LLC is seeking a Software Engineer to build and deploy AI-enabled applications in collaboration with AI Engineers and product teams. The role focuses on application architecture, project scaffolding, enterprise integration, and ensuring deployment readiness for AI use cases.
Responsibilities:
- Architect and build high performance, scalable and secure AI solutions
- Introduce and implement software engineering best practices (architecture/design patterns, building scalable, high performant and secure solutions)
- Responsible for code reviews and scalability and security of production deployed systems
- Integrate AI solutions with UAIS and other systems to enable secure enterprise deployment
- Select and apply the right technical patterns for AI solutions in partnership with AI Engineers
- Scaffold projects, repositories, pipelines, environments, and shared services needed for delivery
- Build core application components, APIs, data integrations, and deployment-ready services
- Partner closely with DevOps and platform teams to ensure secure, scalable, and supportable deployments
- Lead CI/CD, testing, release processes, and operational readiness for MVP and production solutions
Requirements:
- Strong software engineering fundamentals with a hands-on builder mindset and experience delivering production-grade applications
- Some who has experience with and introduced software engineering best practices (architecture/design patterns, building scalable, high performant and secure solutions) to AI engineering teams and AI solutions
- Practical experience working on AI solutions alongside AI Engineers, with understanding of common patterns such as RAG, agentic workflows, API-based model integration, and evaluation or observability needs
- Strong Azure experience across infrastructure, platform services, security, identity, and networking
- Experience with DevOps tooling, CI/CD pipelines, environment management, and secure deployment practices
- Strong experience with open source and cloud technologies such as Neo4j, Cosmos DB, PostgreSQL, MongoDB, Kafka, Containers, K8s, FastAPI, and related application frameworks
- Strong understanding of data platform choices, including when to use relational, NoSQL, graph, vector, and event-driven architectural patterns