Gen AI)

Morgan Stanley•New York, NY

2d•$120,000 - $165,000

About The Position

Design, develop, maintain, and support applications and frameworks powering the firm's Knowledge Management ecosystem. -access ecosystem. Own end-to-end engineering and operational lifecycles for key platforms including Enterprise wiki systems such as Confluence, Q&A tools such as Stack Overflow for Enterprise and Gen AI Search. -to-end engineering and operational lifecycle for key platforms including Build integrations and tools that improve content lifecycle management, governance, user experience, and platform discoverability. Develop automation, scripts, and self-service tools to improve platform reliability, monitoring, and operational efficiency. -service tools to improve platform reliability, monitoring, and operational efficiency. Provide L2/L3 support, including troubleshooting complex issues, identifying root causes, and implementing long-term fixes. -term fixes. Partner with help-desk teams to deliver technical documentation, onboarding materials, and platform guidance. Participate in Agile ceremonies, contribute to backlog refinement, and collaborate with global stakeholders on platform enhancements. Support light integrations with enterprise search and emerging AI-driven features (metadata enrichment, semantic tagging, summarization). -driven features (metadata enrichment, semantic tagging, summarization).

Requirements

Bachelor's degree in computer science, Software Engineering, Information Technology, or related field
5+ years of experience in software development or knowledge/content management platform engineering especially with products such as Confluence, Stack Overflow management platform engineering-management platform engineering
Strong problem-solving and analytical skills
Proficiency with scripting and automation (Python strongly preferred)
Experience with DevOps tools, CI/CD pipelines, and operational automation
Familiarity with Agile methodologies and tools such as Jira
Experience working across both Unix/Linux and Windows environments
Solid understanding of software development lifecycle, service-oriented architecture, design patterns, and Git oriented architecture, design patterns, and Git
Experience with LDAP, Active Directory, PostgreSQL, MongoDB, Redis, or related platform technologies
Knowledge of Docker, Kubernetes, and cloud platforms such as AWS or Azure
Experience working with Microsoft Copilot and Model Context Protocol (MCP), including leveraging APIs to integrate AI-driven capabilities into engineering workflows

Nice To Haves

Background in analytics, statistics, or visualization
Familiarity with enterprise search platforms or LLM/AI assisted features using Open AI, Gemini or other open-source models-assisted features
Experience supporting large enterprise user bases and global operations

Responsibilities

Design, develop, maintain, and support applications and frameworks powering the firm's Knowledge Management ecosystem
Own end-to-end engineering and operational lifecycles for key platforms including Enterprise wiki systems such as Confluence, Q&A tools such as Stack Overflow for Enterprise and Gen AI Search
Build integrations and tools that improve content lifecycle management, governance, user experience, and platform discoverability
Develop automation, scripts, and self-service tools to improve platform reliability, monitoring, and operational efficiency
Provide L2/L3 support, including troubleshooting complex issues, identifying root causes, and implementing long-term fixes
Partner with help-desk teams to deliver technical documentation, onboarding materials, and platform guidance
Participate in Agile ceremonies, contribute to backlog refinement, and collaborate with global stakeholders on platform enhancements
Support light integrations with enterprise search and emerging AI-driven features (metadata enrichment, semantic tagging, summarization)

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