[Hiring] Full Stack Engineer, AI systems @Bjak

Role Description

A1 is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.

We are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users.

• Build end-to-end product features across frontend, backend, and AI integrations
• Design agent workflows that handle planning, tool use, failure, and recovery across multiple steps
• Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditions
• Design real-time AI interactions with streaming, partial results, and tight latency constraints
• Improve system reliability, observability, and fallback mechanisms
• Collaborate closely with ML, backend, and product teams to ship features end-to-end
• Continuously iterate based on real usage and failure modes

Qualifications

• Strong experience in full stack engineering (frontend + backend)
• Solid understanding of system design and API architecture
• Experience working with LLMs, RAG systems, or AI-powered applications
• Ability to handle ambiguity and make pragmatic engineering decisions
• Strong ownership - able to take features from idea to production
• Comfort working in fast-moving environments with evolving requirements

Requirements

• Own and ship AI-native product features that move beyond chat into persistent, goal-driven workflows
• Design and deploy agent workflows that reliably complete multi-step tasks across tools and sessions
• Reduce latency and improve responsiveness of AI interactions while maintaining output quality
• Build robust fallback and recovery mechanisms for LLM and tool failures in production environments
• Improve the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoring
• Establish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systems
• Contribute to a product experience where AI feels proactive, consistent, and dependable over time

Benefits

• The best products today in the world were built by small, world class teams
• High talent density and hands-on team
• Collective decision-making and rapid speed
• Balance between shipping high quality work and learning
• Ability to bring structure, exercise judgment, and execute independently
• Goal to provide users with a truly magical product

Tech Stack

• Next.js
• Python
• NodeJs
• Pytorch
• OpenAI / Anthropic / open-source LLMs
• SQL & noSQL
• Kubernetes
• Docker

Interview Process

• If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews
• Applications are evaluated by our technical team members
• Interviews will be conducted via virtual meetings and/or onsite
• We value transparency and efficiency, so expect a prompt decision
• If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us
• This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally