The Role:
We are seeking an AI Agent Engineer to design, build, and operationalize AI-powered agents that enhance employee productivity and decision-making in a complex enterprise environment. The ideal candidate combines strong AI/ML foundations, hands-on experience with agent frameworks, and a pragmatic approach to delivering business value in partnership with cross-functional teams.
Experience with Glean (or similar enterprise AI search/assistant platforms) is a strong plus.
What You'll Do:
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Design and develop AI agents
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Engineer and implement AI agents and workflows that automate and augment knowledge work.
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Translate business requirements into robust agent designs, including tool orchestration, routing logic, and guardrails.
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Prototype quickly, then harden solutions for reliability, scalability, and maintainability.
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AI/ML and platform integration
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Leverage LLMs and related AI services (e.g., retrieval-augmented generation, embeddings, vector search) to power agent capabilities.
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Integrate agents with enterprise systems, APIs, and data sources (e.g., collaboration tools, knowledge repositories, ticketing systems).
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Partner with platform teams (e.g., Glean, M365, internal APIs) to ensure secure and compliant integrations.
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Agent lifecycle management
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Define and implement monitoring, logging, and feedback loops to continuously improve agent performance.
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Establish and maintain evaluation frameworks, metrics, and test harnesses for AI agent behavior and output quality.
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Document agent architectures, decision logic, and dependencies for support and future enhancements.
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Collaboration and ways of working
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Collaborate closely with engineers, architects, data teams, and business SMEs in a highly matrixed, global environment.
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Contribute to shared patterns, reusable components, and best practices for AI agent development.
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Champion responsible AI, including security, privacy, compliance, and user trust considerations.
Your Skills & Abilities (Required Qualifications):
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Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; or equivalent practical experience.
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3–7+ years of professional software engineering or AI/ML engineering experience in complex, enterprise environments.
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Strong proficiency in at least one modern programming language (e.g., Python, TypeScript/JavaScript, Java).
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Hands-on experience with LLM-based applications, AI frameworks, or agent tooling (e.g., LangChain, Semantic Kernel, custom orchestration frameworks).
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Solid understanding of Prompt engineering and retrieval-augmented generation (RAG), RESTful APIs and integration patterns, and Data structures, algorithms, and basic ML/LLM concepts.
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Experience building production services (microservices or serverless) with appropriate observability and testing.
What Will Give You A Competitive Edge (Preferred Qualifications):
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Experience with Glean or similar enterprise AI search/assistant platforms (e.g., integrating sources, configuring tools, designing agents or workflows within the platform).
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Experience with Microsoft 365 and AI assistants (e.g., Copilot) or other enterprise collaboration ecosystems.
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Familiarity with Enterprise identity and access management concepts (e.g., RBAC, least privilege), Observability and telemetry for AI systems (e.g., logging, tracing, quality dashboards), and experimentation and A/B testing for AI features.
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Background in user-centric design or close collaboration with UX teams for AI experiences.
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