Sr Full-Stack AI Engineer (Remote)

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 ----- 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 ----- 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 ----- 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