Job Description

Description


About Superbench


Superbench is building the next generation of AI-powered sales and operations software for service businesses. We help companies that rely on inbound conversations - across WhatsApp, web chat, and other messaging channels - convert more leads, automate manual sales work, and operate more efficiently using conversational AI and real-time analytics.


Our platform combines an AI-native CRM, conversational sales agents, scheduling automation, and marketing analytics into a single system that directly impacts revenue for our customers. As we pivot and double down on AI-enabled product development, we're rebuilding our engineering foundation to move faster, ship higher-quality software, and turn ambitious product ideas into production-ready systems.


About the Role


As Lead Full-Stack Engineer, you will be the most senior full-time engineer at Superbench, working closely with the CEO, CPO, and CTO to define and execute the company's technical direction. This is a hands-on leadership role for someone who thrives in early-stage environments, enjoys owning systems end-to-end, and can turn ambiguity into well-structured, scalable solutions.


You'll be responsible not just for writing code, but for raising the engineering bar across the company - shaping architecture, improving reliability, guiding other engineers, and helping Superbench transition from scrappy builds to a robust, scalable platform.


  • Own the design and implementation of core backend and frontend systems across the Superbench platform
  • Lead architectural decisions across APIs, services, databases, and integrations, with a strong focus on scalability, reliability, and maintainability
  • Build and evolve AI-powered customer-facing features, including conversational flows, RAG pipelines, and agentic systems
  • Work hands-on across the stack: Node.js/TypeScript and Python backend services, React frontend applications, and supporting infrastructure
  • Improve engineering standards around testing, observability, code quality, and deployment practices
  • Lead and mentor a small engineering team through technical direction, code reviews, and day-to-day guidance
  • Collaborate closely with product and leadership to translate business goals into clear technical plans and execution
  • Take ownership of cloud infrastructure, CI/CD pipelines, and DevOps practices to support rapid, safe iteration
  • Play a key role in rebuilding and strengthening the engineering function as the company pivots and scales

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Requirements


We are looking for a Lead Engineer who is excited to face challenges head-on, take ownership of the tech stack, and make key technical decisions to drive Superbench forward.

Note:


While this role is remote, it is only open to candidates that are within ±3 hours of Singapore time zone (SGT), as this is where our offices are headquartered and all stakeholders are located.


Must have:


  • 8+ years of professional software engineering experience, with a strong focus on building and operating production systems
  • 6+ years of backend engineering experience, primarily using Node.js frameworks (e.g. Express, NestJS) and modern TypeScript
  • 4+ years of frontend engineering experience building user-facing applications with React
  • Deep understanding of JavaScript and TypeScript
  • Strong experience designing and building scalable backend architectures, APIs, and services with clear ownership and reliability in mind
  • Solid experience with relational databases (e.g. PostgreSQL, MySQL), including schema design and query optimization
  • Hands-on experience with NoSQL databases (e.g. MongoDB)
  • Hands-on Python experience (2+ years), particularly for data processing, AI workflows, or backend services
  • Practical experience integrating AI into customer-facing products, including:
    • Vector embeddings and similarity search
    • Retrieval-Augmented Generation (RAG) pipelines
    • Agentic or multi-step AI workflows
    • AI frameworks and tools such as OpenAI SDK, LangGraph, MCP, or similar
  • Hands-on experience with vector databases (e.g. Pinecone or equivalents) in production or near-production systems
  • Experience working with cloud platforms, preferably Google Cloud Platform (GCP), including:
    • Infrastructure-as-code (e.g. Terraform)
    • CI/CD pipelines and automated deployments
    • Operational best practices (monitoring, logging, incident response)
  • Strong understanding of DevOps practices, including environment management, release processes, and observability
    • Containerization and deployment using Docker, including building, versioning, and running production-ready images
    • Proven experience designing, implementing, and maintaining CI/CD pipelines for automated testing, builds, and deployment
    • Solid understanding of observability in production systems, including metrics, structured logging, distributed tracing, and alerting to support reliability and incident response
  • Proven experience leading or mentoring engineers, making technical decisions, and setting engineering standards
  • Comfortable working in an early-stage startup environment with ambiguity, shifting priorities, and high ownership
  • Strong communication skills, with the ability to explain technical decisions to both technical and non-technical stakeholders
  • Strong spoken and written English

Nice to have:


  • Prior experience as a Lead Engineer, Staff Engineer, or early engineering hire at a startup
  • Experience rebuilding or significantly improving an existing codebase or engineering culture
  • Familiarity with event-driven architectures, background jobs, or message queues
  • Experience building real-time or conversational systems (e.g. chat, messaging, CRM, workflow automation)
  • Exposure to analytics, data pipelines, or reporting systems
  • Experience working with multi-tenant SaaS platforms
  • Familiarity with security best practices, authentication/authorization, and data privacy considerations
  • Previous experience working with global or remote-first teams

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About the interview process:


1. Basic-fit and screening interview (20-30 minutes)


A conversation with our CEO to get to know you better and understand your background.


  • Review your experience and technical depth at a high level
  • Discuss your interest in Superbench and early-stage roles
  • Assess alignment with our team, culture, and expectations

2. Take-home assessment (3-4 hours)


A practical, real-world project designed to evaluate how you think and build across both backend and frontend.


  • Focus on architecture, code quality, and decision-making
  • Reflects the types of problems you'd work on at Superbench
  • We value clarity and trade-offs, not perfection

3. Technical interview (90 minutes)


A live technical session with our CTO to walk through your take-home submission.


  • Deep dive into your implementation and architectural choices
  • Discussion of backend, frontend, and AI-related decisions
  • Explore improvements, alternatives, and trade-offs
  • Live problem-solving or extension of your solution

4. Deep dive interview (45-60 minutes)


A final conversation with our CPO focused on leadership, ownership, and long-term fit.


  • Review past roles, decisions, and lessons learned
  • Discuss how you lead, mentor, and make technical calls under uncertainty
  • Align on expectations and what success looks like in this role

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Benefits


Flexibility & Work Style


  • Fully remote role with a distributed team
  • Flexible working hours - we care about outcomes, not clock-watching
  • Autonomy to structure your day, with clear communication and accountability

Ownership & Impact


  • A true leadership role in an early-stage startup
  • Ownership over core technical decisions during a critical company pivot
  • Direct influence on product direction, architecture, and long-term technical strategy

Compensation & Equipment


  • Competitive compensation, commensurate with experience and seniority
  • MacBook Pro provided

Time Off


  • Unlimited PTO (after a 3-month probationary period)

Growth & Learning


  • Grow into a long-term technical leader as the company scales
  • Deepen your expertise in AI-first product development, including conversational AI, RAG, and agentic systems
  • Work closely with founders and leadership
  • Freedom to experiment, learn, and introduce better tools, processes, and practices

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