SB01 - Senior Agentic AI Engineer - Azure
About the Project
We are partnering with a fast-growing AI-native software organization building enterprise-grade intelligent workflow systems on top of the Microsoft AI ecosystem. The company operates in a high-velocity environment where generative AI is embedded directly into engineering, delivery, and operational processes rather than treated as a standalone experimentation layer. The organization is investing heavily in agentic software architectures designed to automate complex business workflows, augment enterprise knowledge operations, and accelerate product delivery cycles across distributed teams. Their engineering culture is deeply automation-oriented, with AI-assisted development workflows considered a core competency rather than an optional productivity enhancement. This initiative sits at the intersection of:
- Enterprise AI orchestration
- Autonomous and semi-autonomous software agents
- AI-accelerated software delivery
- Secure cloud-native infrastructure
- Scalable developer productivity systems
- Governance-aware AI implementation The environment is highly execution-focused and optimized for rapid iteration. Engineering teams are expected to leverage AI-assisted coding workflows extensively as part of day-to-day delivery operations. Internal development standards assume that a significant percentage of implementation work is generated, refined, validated, and orchestrated through AI-enabled tooling pipelines. The broader platform strategy is centered around the Microsoft AI stack, including enterprise-grade orchestration, secure model integration, cloud-native AI services, and multi-agent workflow execution. The company is intentionally avoiding fragmented multi-cloud AI experimentation in favor of a tightly governed Azure-centric operating model focused on scalability, compliance, observability, and enterprise deployment readiness. This role is part of a broader initiative to operationalize AI-native software engineering at scale.
Role and Responsibilities
As an Agentic AI Engineer, you will help design and implement production-grade AI systems using the Microsoft ecosystem as the primary development and deployment platform. You will operate inside a modern AI-assisted engineering environment where developer productivity is tightly integrated with copilots, autonomous coding workflows, and intelligent orchestration systems. Key responsibilities include:
- Designing and implementing multi-agent AI systems for enterprise workflows
- Building AI-native backend services and orchestration layers on Azure
- Developing secure integrations between LLM-powered agents and enterprise systems
- Creating scalable architectures for autonomous task execution and reasoning workflows
- Leveraging AI-assisted development environments as part of standard engineering delivery
- Operating within AI-first software development lifecycles where code generation, refactoring, and validation are heavily AI-augmented
- Building reusable frameworks and tooling for internal AI engineering acceleration
- Collaborating with platform, product, and infrastructure stakeholders on production deployment strategies
- Implementing governance, observability, and reliability standards for AI systems
- Participating in architecture reviews, technical strategy discussions, and AI capability roadmapping
- Contributing to internal standards around responsible AI usage, developer enablement, and operational resilience The environment requires engineers who are comfortable moving between platform engineering, applied AI implementation, workflow orchestration, and developer productivity optimization.
What We’re Looking For
Must-Haves
- Strong hands-on experience building AI systems on Microsoft Azure
- Deep familiarity with Azure-native AI services and agent orchestration patterns
- Proven experience designing or implementing agentic AI workflows
- Strong proficiency with AI-assisted software engineering workflows
- Daily usage of AI coding copilots within modern IDE environments
- Experience working in highly iterative, AI-accelerated engineering teams
- Strong backend engineering and cloud architecture fundamentals
- Experience integrating LLMs into production systems
- Practical understanding of secure enterprise AI deployment patterns
- Experience building APIs, orchestration layers, and event-driven systems
- Comfort operating in fast-moving, ambiguous, high-ownership environments
- Strong communication skills across technical and non-technical stakeholders
- Ability to evaluate, validate, and refine AI-generated code at production quality standards
Nice-to-Haves
- Experience with multi-agent orchestration frameworks
- Exposure to enterprise governance and compliance requirements for AI systems
- Familiarity with retrieval pipelines, memory systems, and context orchestration
- Experience designing internal AI developer tooling
- Background in platform engineering or developer infrastructure
- Experience with enterprise copilots, workflow automation, or knowledge systems
- Understanding of observability, evaluation, and reliability patterns for LLM applications
- Prior work inside AI-native or automation-first engineering organizations
- Microsoft AI or cloud certifications
- Experience supporting globally distributed engineering environments
Why Join Us?
This is an opportunity to join a company operating at the frontier of AI-native software delivery. The organization has already moved beyond experimentation and is actively operationalizing AI across engineering, product development, and internal workflows. Teams are building systems where AI is embedded directly into execution layers, developer tooling, and operational decision-making. You will work alongside senior technical operators who view AI not as an enhancement layer, but as foundational infrastructure for modern software organizations. Highlights include:
- High-impact work on production AI systems
- Exposure to advanced agentic architectures and enterprise AI workflows
- AI-first engineering culture with strong technical ambition
- Significant ownership and technical influence
- Modern cloud-native engineering practices
- Opportunity to shape internal standards for AI-enabled software delivery
- Strong emphasis on execution velocity and technical innovation
- Access to complex enterprise-scale implementation challenges
- Collaborative environment with deep investment in developer productivity and automation This role is best suited for engineers who are excited about the future of autonomous systems, AI-assisted development, and enterprise-scale agent orchestration.
Application Instructions
Please submit:
- An updated resume or professional profile
- A brief overview of your experience with Azure-based AI systems
- Examples of agentic AI projects, orchestration workflows, or AI-assisted engineering implementations
- Details on your experience using AI coding copilots in production environments
- Any relevant GitHub repositories, technical writeups, demos, or architecture samples