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 a Senior Full-Stack AI Engineer, you will play a critical hands-on role in building and evolving Superbench’s AI-powered platform. Working closely with product and leadership, you will design, develop, and ship intelligent, customer-facing features that leverage modern AI capabilities.
This role is ideal for someone who is deeply experienced in applying AI in production environments, especially in building multi-step, multi-agent workflows, and who is equally comfortable working across the full stack. You will help turn ambiguous product ideas into reliable, scalable systems, with a strong focus on delivering real user value through AI.
You’ll contribute across backend, frontend, and AI systems - owning features end-to-end while collaborating with other engineers to maintain high standards in code quality, performance, and usability.
- Design and build AI-powered product features, including conversational interfaces, RAG pipelines, and multi-step / multi-agent workflows
- Own the implementation of backend and frontend systems across the Superbench platform
- Translate product requirements into scalable technical solutions, particularly for AI-driven use cases
- Work hands-on across the stack: Node.js/TypeScript and Python backend services, React frontend applications
- Integrate LLMs and AI tooling into production systems, ensuring reliability, performance, and strong user experience
- Build and maintain APIs, services, and data pipelines that support AI functionality
- Collaborate closely with product and design to iterate quickly on AI-driven features
- Contribute to engineering best practices around testing, code quality, and system reliability
- Participate in code reviews and support knowledge sharing across the team
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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:
- 6+ years of professional software engineering experience, with a strong focus on building production systems
- 4+ years of backend engineering experience, primarily using Node.js frameworks (e.g. Express, NestJS) and modern TypeScript
- 2+ years of frontend engineering experience building user-facing applications with React
- 2+ years of practical experience building and integrating AI systems into production applications
- Deep understanding of JavaScript and TypeScript
- Strong experience designing and building scalable backend systems, APIs, and services
- 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 AI workflows, data processing, or backend services
- Strong experience building AI-powered customer-facing features, including:
- Retrieval-Augmented Generation (RAG) pipelines
- Multi-step and/or multi-agent AI workflows
- Prompt design, evaluation, and iteration
- Tool-using agents and orchestration frameworks
- Experience working with AI frameworks and tools such as OpenAI SDK, LangGraph, MCP, or similar
- Hands-on experience with vector databases (e.g. Pinecone or equivalents)
- Proven experience integrating complex AI flows into real user-facing products
- Strong problem-solving skills and ability to work in ambiguous environments
- Strong communication skills, with the ability to explain technical concepts clearly
- Strong spoken and written English
Nice to have:
- Experience working in early-stage startups or fast-paced product environments
- Familiarity with cloud platforms (e.g. GCP), CI/CD pipelines, and basic DevOps practices
- Experience with event-driven architectures, background jobs, or message queues
- Experience building real-time or conversational systems (e.g. chat, messaging, 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
- Experience collaborating in remote or distributed 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, as well as integrating AI into customer-facing applications.
- Focus on architecture, code quality, effective use of AI, 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