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Lead AI Architect

Job in Town of Italy, Penn Yan, Yates County, New York, 14527, USA
Listing for: Block Labs
Full Time position
Listed on 2025-12-19
Job specializations:
  • IT/Tech
    AI Engineer, Systems Engineer, Data Engineer
Job Description & How to Apply Below
Location: Town of Italy

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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 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

We are building platforms where artificial intelligence is the core engine behind the system. These products involve large‑scale automation, decision‑making processes, and multiple intelligent components that must work together with consistency. We need someone who has real experience designing such systems and can distinguish between a clever demonstration and a production‑ready architecture.

As Lead AI Architect you will design the AI foundation for several automation‑focused products, defining how the system gathers information, reason about it, checks its own work, escalates to humans when needed, and deals with uncertain situations without breaking down.

Working closely with senior engineers, you will convert complex workflows into predictable and observable processes powered by advanced models. This is a system architecture role, not a prompt‑writing role. It requires a deep understanding of large‑scale artificial intelligence design and comfort with setting the technical direction.

Key Responsibilities
  • 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., Lang Graph, Lang Chain, Auto Gen, 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.
  • Maintain visibility into the cost profile of artificial intelligence systems and ensure design choices support predictable spend, scalability, and long‑term sustainability.
About You
  • 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…
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