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Replicant

Automated conversational AI for customer service

Engineering Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of experience managing engineers or engineering teams.
  • At least 10 years of experience in a technical field, such as software engineering.
  • A track record of hiring, developing, and managing the performance of strong technical talent.
  • Experience owning team budget and headcount planning.
  • Demonstrated hands-on fluency with modern artificial intelligence tools through practical work and a demonstrable example.
  • A history of delivering software predictably with a team.
  • Technical depth in system design and tradeoffs sufficient to earn credibility with senior engineers.
  • Experience partnering closely with Product and other cross-functional teams.
  • Ability to use modern artificial intelligence tools extensively and explain what was built, which models were used, and what worked or did not work.
  • Ability to reason about technical tradeoffs, priorities, and risk while trusting senior individual contributors to own code details.
  • Ability to build trust, grow careers, and lead senior engineers effectively.
  • Ability to maintain a customer focus and close the loop after shipping.

Responsibilities

  • Lead a Product Engineering squad of approximately 8 to 15 engineers across projects and products on the platform.
  • Own team budget and headcount planning.
  • Hire engineers, develop existing team members, make timely decisions when someone is not the right fit, and maintain a high hiring bar.
  • Create an environment that motivates engineers, promotes speed, and challenges existing practices.
  • Turn individual artificial intelligence experimentation into team-level improvements in throughput, quality, and time from idea to production, and model this approach.
  • Drive predictable, high-quality delivery of work that matters to customers and stand behind team timelines.
  • Ensure the team shapes product solutions to customer problems, stays close to customers, and stays close to the bots it ships.
  • Invest in testing and validation that provide confidence in production, a fast and effective developer experience, and customer-facing quality.
  • Participate as a peer on the engineering-management team, covering team rituals, one-to-ones, and on-call during transitions and leave.
  • Contribute to joint engineering-department decisions and ownership, including hiring standards and interview processes; career ladders, leveling, and competency frameworks; roadmap development and prioritization; quarterly objectives and key results; testing and validation standards; platform and agent quality; bot-building and delivery processes; developer experience and artificial intelligence enablement; organizational design, on-call and incident culture; and capacity planning.
  • Attend several short, high-intensity management-team working sessions each week, make decisions and take action, and maintain a decision journal.
  • Disagree and commit, provide direct feedback early, and support decisions once made.

Desired Qualifications

  • Experience in conversational artificial intelligence, voice or telephony, machine-learning systems, or real-time infrastructure.
  • Experience building or scaling testing and validation for artificial intelligence or nondeterministic systems.
  • Comfort working in a lean, fast-moving, remote startup with ambitious priorities and a high bar.

About the Company

Replicant

Automated conversational AI for customer service

Replicant provides cloud-based conversational AI for customer service. It builds automated chat and voice agents that handle customer inquiries, answer questions, and resolve problems without human intervention, as a service (subscription). How it works: clients integrate Replicant’s AI into their contact channels (phone, chat, etc.), and the system uses natural language understanding to interpret queries, generates responses, and can hand off to human agents if needed; data is stored and analyzed to improve performance, with a focus on anonymous data usage for privacy. How it differs: emphasizes privacy and data security, offering anonymous data handling, and a subscription model with options to upsell or add features; serves a wide range of industries from retail to banking, aiming to automate end-to-end customer support. Goal: help businesses cut costs and boost efficiency by automating customer service interactions while protecting user privacy.

Company size
51-200
Company stage
Series B
Total funding
$120M
Headquarters
San Francisco, CA
Founded
2017

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