About Block Labs
Block Labs is a premier technology studio operating at the bleeding edge of Web3, Artificial Intelligence, and iGaming. We don't just ship features; we engineer high-scale, production-grade platforms that power the next generation of digital products.
We are a collective of senior engineers, product strategists, and builders who refuse to compromise on architecture. Whether we are designing autonomous multi-agent AI systems, building decentralized financial infrastructure, or architecting high-frequency iGaming platforms, our standard is excellence.
We move fast, but we build for the long term. If you are looking to work alongside a team that values deep technical expertise, thoughtful system design, and product ownership, Block Labs is where you belong.
About The Role
This role sits at the centre of that approach. We are building systems where artificial intelligence is not a minor enhancement but the operational core. These platforms rely on multi-step reasoning, orchestration across several intelligent components, and predictable behaviour at scale. To create this properly, we need someone who has built these kinds of systems before, understands how they work beyond demos, and is comfortable designing and implementing the foundations for long-term growth.
You will be the first AI hire at Block Labs and will play a defining role in shaping the company’s AI capabilities. You will work closely with senior engineers and leadership to turn complex requirements into production-grade systems, and you will influence the architecture that future engineers and architects will build upon.
As Lead AI Engineer, you will own the design and implementation of our AI automation engines. You will build multi-agent workflows, reasoning pipelines, trust layers, orchestration logic, and the supporting systems that allow AI to behave deterministically in the real world.
This is a hands-on role for someone capable of both engineering and architectural design. You will prototype, validate, and build the first versions of several AI platforms, setting the patterns and foundations that others will follow. You will partner with backend, data, and product teams to integrate AI-driven components into large-scale operational systems.
Key Responsibilities:
- Lead the development of AI automation systems, including multi-agent workflows, orchestration logic, and structured reasoning processes.
- Design the foundational architecture for AI-driven platforms, establishing clear engineering patterns and standards for future teams.
- Build core components such as retrieval flows, decision-making pipelines, evaluation layers, safety controls, and human-in-the-loop mechanisms.
- Define approaches for agentic workflows, inter-process coordination, and the deterministic execution of complex tasks.
- Develop verification and trust layers including fact-checking pipelines, validation logic, guardrails, and output monitoring.
- Collaborate with backend and data engineering teams to integrate AI systems with APIs, services, event-driven architectures, and data pipelines.
- Ensure all AI components are measurable, observable, and reliable, establishing SLAs and operational metrics.
- Guide model selection, fine-tuning strategy, retrieval and memory approaches, and long-term evaluation methodologies.
- Contribute to architectural planning, system documentation, and strategic technical direction across the organisation.
- Maintain visibility into AI operational costs and ensure engineering decisions support scalability and predictable spend.
What kind of culture can I expect?
Mature, mission-driven, and low-ego. We value clarity over noise, outcomes over theatrics, and pace without chaos. If you’re one of the smartest minds in your craft and want to build with other experts, you’ll feel at home here.
About You:
- Several years of experience building and deploying ML or LLM-powered systems in production environments.
- Proven experience developing multi-step or agentic workflows, including orchestration, retrieval, tool use, and safety layers.
- Strong engineering skills in Python or another backend language, with a track record of delivering production systems.
- Understanding of distributed system design, microservices, workflow automation, and event-driven architectures.
- Ability to design architectural foundations while also implementing the systems needed to validate them.
- Comfortable operating as the first AI engineer, making decisions that shape the long-term platform.
- Skilled at turning unclear or complex requirements into predictable, observable, and maintainable systems.
- A pragmatic, ownership-driven mindset with a passion for building intelligent, reliable, and scalable automation.
