Kubernetes Security Engineer
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This is a great opportunity for an experienced senior level Software Engineering Lead to use their experience with generative AI to design, build, and scale AI driven applications that deliver measurable business outcomes. This role is a blend of hands-on architecture, development, coaching and mentoring, technical leadership, client-facing execution, and a strong emphasis on Azure-based AI platforms, LLM integrations, and agentic systems for fast AI experimentation pilots. If you are a software engineering lead professional who is on the leading edge of AI and building efficiency, this is a great opportunity., * Must have 10+ years' experience in full stack software engineering
- Must have 5+ years' experience as a software development lead
- Must be able to serve as technical lead / SME across an organization's AI tools and services
- Must have experience delivering multiple AI use cases into production at scale
- Must have a solid understanding and experience with generative AI in the software development space
- Must be able to architect and deliver production-grade LLM-powered applications, including chat, document intelligence, and agentic workflows
- Must be able to mentor onshore and offshore engineering teams on use of AI to improve code quality, architecture discipline, and delivery velocity
- Must be able to design scalable, secure, cloud-native systems using Azure, Docker, Kubernetes, and event-driven architectures
- Programming experience with Python, C#, JavaScript/TypeScript, SQL is ideal
- AI experience with Azure Foundry, LangGraph, Semantic Kernel, DSPy, and LLM prompt engineering is ideal
- Experience with cloud and devops technologies like Azure, Docker, Kubernetes, CI/CD, Terraform, and Jenkins is ideal
- Experience with frameworks and APIs including .NET, FastAPI, Node.js, GraphQL, and React is ideal
- Any experience with data and search technologies like Snowflake, Databricks, PostgreSQL, SQL Server, and Azure AI Search is a plus
- Must be able to design and implement prompt engineering, evaluation frameworks, and observability for AI systems
- Must be able to ensure enterprise standards for authentication, authorization, and system integration
- Must be able to collaborate on requirements gathering, solution design, and development with other IT app dev and business stakeholders
- Must be able to translate business problems into AI-enabled and agentic solutions
- Must be able to design systems capable of processing high-volume documents and transactions with accuracy and traceability
- Must be able to continuously iterate solutions based on real-world usage and feedback
- Must be a self-starter who can work independently but also with a team with little oversite
- Must be able communicate with various IT teams as well as business stakeholders on occasion