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As a Forward Deployed Engineer II (FDE II) in the Microsoft 365 Growth + Incubation engineering team, you will work hands-on with customers and partners to accelerate the adoption of Copilot solutions. In this role, you will engage in complex and ambiguous technical scenarios where existing guidance may be incomplete, applying strong engineering and architectural judgment to help customers and partners design secure, scalable, and effective agentic solutions. Your work will center on unblocking technical friction, validating design decisions, and enabling sustained adoption. You will apply software engineering and systems architecture skills to guide technical decision-making, explore design tradeoffs, and validate approaches through hands-on experimentation, proof-of-concept work, and example implementations. You will work closely with customer and partner engineering teams to accelerate learning, contribute to reference architectures and reusable design patterns, and ensure solutions align with Microsoft best practices, security expectations, and Responsible AI requirements. You will join a collaborative engineering team within the Microsoft 365 Growth & Incubation organization, working in a One Microsoft model across product, engineering, and field teams. The team culture values curiosity, accountability, and continuous learning, and provides opportunities to grow technical depth and influence over time.
Job Responsibility:
Contribute to solution architecture for agent-based Copilot solutions, supporting discovery, design, and deployment readiness under guidance from senior engineers
Assist in developing reference architectures, extensibility frameworks, and reusable design templates, contributing technical input and implementation examples
Work alongside customer and partner developers during sprints, shadow build cycles, and design reviews to learn patterns and help unblock technical issues
Write, review, and validate code in support of proofs of concept, reference implementations, and architectural validation
Support structured validation and user acceptance activities, helping gather technical findings and feedback from customer and partner environments
Identify integration challenges and implementation risks, escalating findings and proposing solutions with guidance
Learn and apply best practices for security, reliability, and scalability in enterprise agent-based solutions
Requirements:
Bachelor's Degree in Computer Science, Engineering, Data Science, Math, Business, or related field AND 2+ years experience in engineering, product/technical program management, data analysis, or product development
OR equivalent experience
Demonstrated ability to design and reason about distributed, enterprise-grade systems, including integrations across cloud, data, and application layers
Hands-on engineering experience, with the ability to write, review, and reason about code to validate designs and resolve complex technical problems
Demonstrated ability to translate customer business requirements into secure, scalable technical architectures
Experience working directly with customers or partners on complex technical problems in a delivery, advisory, or enablement capacity
Ability to lead technical discussions with both senior technical and business stakeholders
Experience working with Microsoft 365 Copilot, Copilot extensibility, or adjacent Microsoft AI platforms
Experience building, extending, or enabling Copilot agents or agent-based solutions, or comparable AI-driven systems
Familiarity with agent-based system design, including orchestration patterns or grounding approaches
Experience producing reference architectures, reusable patterns, or technical playbooks
Hands-on experience building or validating proofs of concept, reference implementations, or technical prototypes
Experience supporting or enabling partner ecosystems such as GSIs, SIs, or ISVs
Experience collaborating closely with product management and product engineering teams, contributing technical input and customer or partner learnings
Exposure to enterprise-scale AI or data-driven systems, including performance, reliability, or operational considerations