Support Software Engineer, Replicant
Offers equity
Call center AI chatbots
Be an early applicant
Call center AI chatbots
101-200 employees
Be an early applicant
Offers equity
101-200 employees
Company mission
To use AI to resolve as many conversations as possible while elevating human agents to do what they are uniquely good at.
Role
Who you are
- Debugging depth. You're comfortable reading unfamiliar code, tracing logs, and reasoning across a genuinely broad surface area: production debugging, distributed systems, REST APIs, and authentication (OAuth 2.0 and similar) are all second nature, and you don't need to be a specialist in just one system
- Agentic fluency. You use agentic coding tools (Claude Code, Cursor, or equivalent) as your default way of investigating and fixing issues, not as a novelty layered on top of how you used to work, and you're just as comfortable maintaining legacy TypeScript code where that's still what's running in production
- Customer-facing strength. You can gather requirements directly from customers, confirm reproduction steps, coordinate tests, and explain a fix in plain language, including with customers who are frustrated that something broke
- Nice to have: experience with LLM prompting or debugging conversational AI/voice systems; experience with enterprise tools like Salesforce, Zendesk, or Jira; experience building internal tooling or automations that reduced manual engineering or support load
What the job involves
- We’re leading the shift from legacy systems to AI-first service, powered by large language models (LLMs) and designed for enterprise scale, security, and empathy
- If you’re excited by the potential of LLMs, voice AI, and building category-defining technology with a kind, ambitious team, you’ll love it here
- Our customers don't just buy an AI agent that works in a demo
- They buy one that keeps resolving calls, holds up under real call volumes, and stays reliable as their business changes underneath it
- As a Support Software Engineer on our Technical Support team, you make that true once a bot or product is live: you own the fixes and enhancements that keep it running, dig through logs, code, and conversation data to find out why something broke, and build the internal tools that make the next investigation faster than the last one
- This is a post-launch engineering role, equal parts investigator, fixer, and customer point of contact, and you are measured on reliability and resolution, not features shipped
- It's also a genuinely broad technical mandate spanning AI Agent behavior, Conversation Intelligence, telephony, integrations, and legacy TypeScript SDK bots and you'll build it on real production traffic, not demos, with real autonomy on a team small enough that your work is visible to customers and leadership alike
- Own the bugs, issues, and enhancement requests for bots and products once they're live in production, working the escalations frontline Support Engineers can't resolve on their own
- Take a holistic view of platform health: AI Agent behavior and configuration, Conversation Intelligence, telephony, SSO and authentication, integrations, API issues, LLM prompting, and legacy FSM AI Agents built in TypeScript
- Investigate root cause across logs, code, and Replicant's internal tooling, then design, implement, test, and ship the fix, using agentic coding tools like Claude Code and Cursor as a core part of how you work
- Serve as the primary point of contact for customers on live issues: gather and confirm requirements on bugs and enhancement requests, and coordinate testing directly with them
- Act as an escalation point for frontline Support Engineers, providing technical context and guidance on the issues they can't close alone
- Build and maintain the internal tools that make the next investigation, fix, or enhancement faster than the last one
- Gather and raise customer feedback to Product, and adhere to team SLAs and support metrics along the way
Our take
Whilst automation and AI are being applied to industries across the world, customers must still endure long waits and inconsistent service from telecom companies. In addition to this, customer service agents must answer the same repetitive questions hundreds of times every day, which is both expensive and inefficient. Replicant uses neural networks to provide completely autonomous call center technology that aims to provide intelligent and human-like alternatives to customer service agents.
Replicant's service understands context, accents, slang, and technical terms, providing far more intelligent results than simple answer-recognition phone services. Although various startups are taking steps towards reducing bottlenecks within customer service calls through autonomous chatbots, Replicant stands out by focusing on realistic, engaging conversation. This is done through its neural networks, providing a convincing replacement that reduces costs and frustrations within call centers of any type.
Replicant has secured a good amount of funding to fuel its ambitions to expand research and development, improve its conversations, and launch new automated channels. The company also plans to increase headcount across a range of teams, onboard new customers, and launch professional development programs for its employees.
Freddie
Company Specialist at Welcome to the Jungle
Insights
62% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Apr 2022
$78m
SERIES B
Sep 2020
$27m
SERIES A
Total funding: $120m
Company benefits
- Company Equity: We view our employees as the true owners of Replicant and offer company equity.
- Health insurance: We offer a competitive package with health, dental, eye care, and retirement benefits.
- Remote-friendly: From the Bay to New Brunswick—we have employees across the world, so you can work wherever works for you!
- Frequent offsites: We take team-building seriously and love working side by side.
- Flexible vacation: Take a break when you need it so you can come back refreshed and ready.
- Sabbatical program: After you’ve worked at Replicant for 5 years, you are eligible to take a sabbatical for up to five weeks.
- Equipment stipend: All employees are set up with the essential equipment, but if you have special requests, you’re provided a stipend to cover these costs.
- Wellness stipend: We want employees to feel empowered to manage your fitness, health, and mental wellbeing so we offer a yearly wellness stipend.
Company HQ
Presidio of San Francisco, San Francisco, CA
Leadership
Gadi Shamia
(Co-Founder & CEO)They co-founded TopManage before spending 6 years at SAP and Magneto, as well as COO positions at Adobe and Talkdesk. They co-founded Replicant in January 2019, serving since as CEO.
Benjamin Gleitzman
(Co-Founder & CTO)Having studied at MIT, they worked as a Software Engineer for Hunch and co-founded NextStep and ShockBottoms. They spent 6 years as an eBay Software Engineer before co-founding Ruse, MONA, and Replicant.
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