Lead AI Architect

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.

This role falls exactly in that area. We are building platforms where artificial intelligence is not a side feature but the core engine behind the system. These platforms involve large scale automation, decision making processes, and multiple intelligent components that need to work together with consistency. To build this properly we need someone who has real experience designing these kinds of systems and understands the difference between a clever demonstration and a production ready architecture.

As Lead AI Architect you will design the artificial intelligence foundation for several automation focused products. You will define how the system gathers information, reasons about it, checks its own work, escalates to humans when needed, and deals with uncertain situations without falling apart.

You will work closely with senior engineers to turn complex workflows into predictable and observable processes powered by advanced models. This is not a prompt writing role. It is a system architecture role for someone who understands large scale artificial intelligence design and is comfortable setting the technical direction.

· Own and evolve the strategy, architecture, and execution of AI-driven automation across the organisation, with a focus on multi-agent systems and end-to-end orchestration.

· Provide hands-on technical leadership, working closely with engineering leads to define standards, patterns, and best practices for deploying LLM-powered services.

· Design scalable AI architectures incorporating model orchestration, agent frameworks, retrieval pipelines, evaluation systems, and human-in-the-loop workflows.

· Lead implementation of agentic frameworks (e.g., LangGraph, LangChain, AutoGen, CrewAI) to support complex task delegation, inter-agent communication, and deterministic reasoning paths.

· Define and maintain a robust “trust layer” including fact-verification, retrieval-augmented generation, validation logic, guardrails, and safety controls.

· Partner with backend and data engineering teams to integrate AI systems with data pipelines, internal APIs, and event-driven architectures.

· Ensure AI services are observable, measurable, and tuned for both performance and accuracy, defining SLAs and operational metrics.

· Guide model-selection, fine-tuning strategies, vector search usage, and knowledge-graph integrations where required.

· Oversee architecture reviews, documentation standards, and long-term AI platform scalability.

· Collaborate closely with security stakeholders to ensure safe, compliant, and privacy-aware operation of all AI systems.

· Represent the AI function in cross-company planning, roadmap discussions, and technical leadership forums.

· Maintaining visibility into the cost profile of artificial intelligence systems and making sure that design choices support predictable spend, scalability and long-term sustainability.

· Several years of experience building and deploying ML or LLM-based systems in production environments.

· Proven experience architecting agentic or multi-step AI workflows, including orchestration, tool-use, retrieval, and safety layers.

· Deep understanding of modern LLM frameworks, vector databases, and retrieval pipelines (e.g., Pinecone, Weaviate, pgvector).

· Familiarity with workflow orchestrators (e.g., Temporal, Dagster, Airflow) and event-driven system design.

· Experience implementing content-safety, compliance, or guardrail systems is a strong advantage.

· Strong understanding of distributed architectures, microservices, and system interdependencies.

· Experience collaborating with cross-functional teams and communicating complex technical concepts with clarity.

· Comfortable leading architecture discussions, making strategic technical decisions, and mentoring engineering teams.

· A proactive, ownership-driven mindset with a passion for building reliable, intelligent, and scalable AI platforms.

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.