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Engineering manager, agent software engineer

Niederdorla
Decagon
Engineering Manager
Inserat online seit: 29 August
Beschreibung

About the TeamThe Agent SWE team at Decagon deploys the most advanced conversational AI agents to our customers that impact millions of users and directly drive Decagon’s growth. You will guide a team to build on our industry-leading AI agent platform, collaborate directly with customers and use your own creativity to devise long-term, scalable solutions that support their needs.Our mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues.About the RoleAs a leader on the Agent Software Engineeirng team, you’ll have complete ownership and autonomy in shipping best-in-class AI agents, from initial implementation through continuous iteration. You’ll work directly with leaders across industries like finance, healthcare and hospitality, solving their users’ needs with reliable and intuitive AI agents.Engineers here own their work end-to-end and are trusted to make a real impact. This role is for someone who is excited to mentor a team of junior engineers, dives deep into complex system challenges and builds elegant solutions that scale to millions of users.In this role, you willLead a team to design and build AI agents that outperform human agents in managing complex customer interactions and driving customer retentionCollaborate closely with enterprise customers across a number of verticals, understand their needs and transform these pain points into magical AI agentsPartner with product, design and research to identify cross-customer trends that guide the evolution of Decagon’s agent building platform and research effortsContribute to team strategy and help define the future of AI customer support agentsYour background looks something like thisHave 1+ years of engineering management experienceHave 5+ years of industry experience in software engineeringProficiency with Python, Typescript and asynchronous programmingA high degree of comfort digging into systems failures within deep technology stacks using any tool necessaryEven betterPrior experience working with multi-modal models #J-18808-Ljbffr

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