AI Architect - Agentic AI

• Design, develop, and deploy production-grade software and AI-driven applications in a cloud-native environment.
• Build and orchestrate agentic AI systems, including multi-step agents, tool and function calling, and retrieval-augmented generation (RAG). These systems should be able to reason, plan, and act across enterprise systems.
• Containerize applications with Docker and deploy and manage them on Kubernetes (AKS).
• Architect scalable, secure solutions on Microsoft Azure, using services such as Azure OpenAI / AI Foundry, Azure Functions, and Azure DevOps.
• Integrate LLM-based agents with internal APIs, data sources, and business workflows.
• Put evaluation, monitoring, guardrails, and observability in place for AI agents running in production.
• Work with architects, data engineers, product owners, and business stakeholders in an Agile environment.
• Contribute to code reviews, technical design, and engineering best practices. Mentor less experienced engineers.

• 10+ years of relevant software engineering experience, including 5+ years in a solution or enterprise architecture role. Experience architecting AI-enabled or AI-native development processes preferred. Cloud-native solution architecture experience preferred.
• Demonstrated ability to design and communicate enterprise-grade solution architectures spanning data, integration, security, and AI-native capabilities.
• Deep working knowledge of AI-assisted software development practices, including agentic coding workflows, context management, and human-AI collaborative planning methods.
• Ability to translate ambiguous business and customer requirements into concrete, testable architecture decisions, and to lead structured, adversarial requirements review to surface gaps before build.
• Strong understanding of secure-by-design principles, threat modeling, and software supply chain risk, with the ability to apply them within a regulated (CMMC / NIST SP 800-171) environment.
• Ability to mentor and elevate the technical judgment of Solution Architects, Enterprise Architects, and senior engineers across the organization.
• Skilled at driving architectural consensus across cross-functional groups, including engineering, product, security, and executive sponsors.
• Ability to evaluate emerging AI development tools and practices critically, distinguishing durable architectural improvement from short-term convenience.
• Ability to demonstrate independent, objective, open-minded thinking with strong attention to detail and sound judgment.
• Must take responsibility for architectural decisions, their rationale, and their downstream consequences.
• Must be dependable, highly reliable, and follow through on commitments across multiple concurrent initiatives.
• Strong skills in at least one modern language, such as Python, C#/.NET, or Java. Python is preferred for AI work.
• Hands-on production experience with Kubernetes and Docker.
• Solid experience building and deploying solutions on Microsoft Azure.
• Demonstrated experience building agentic AI applications. This includes LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or similar, as well as tool use, memory, and multi-agent patterns.
• Experience with RAG pipelines, vector databases, and prompt engineering.
• Working knowledge of CI/CD pipelines, Git, and infrastructure-as-code (Terraform, Bicep, or ARM).
• Strong communication skills and the ability to work independently in a remote setting.

Preferred Qualifications

• Experience with Azure OpenAI Service, Azure AI Foundry, or Azure AI Search.
• Background in maritime, offshore, energy, or other engineering-driven or regulated industries.
• Familiarity with MLOps/LLMOps practices and with AI evaluation and safety frameworks.
• Relevant certifications, such as Azure Developer (AZ-204), Azure AI Engineer (AI-102), or CKA/CKAD.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.