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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