Architect Jobs

About The Position

Requirements

• Deep Python engineering experience and a track record of shipping production systems.
• Significant experience with applied ML, LLM systems, NLP, retrieval, embeddings, ranking, or agentic architectures.
• Strong system-design skills and the ability to reason about tradeoffs across accuracy, latency, cost, reliability, and maintainability.
• Experience building evaluation pipelines, offline and online metrics, model monitoring, or data feedback loops.
• Ability to operate independently in ambiguous environments and drive complex projects to completion.
• Strong technical judgment and the ability to distinguish promising AI techniques from fragile demos.
• Clear communication and mentorship skills.
• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent industry experience.

Nice To Haves

• Experience building production LLM applications, AI agents, RAG systems, or enterprise automation platforms.
• Experience with financial services, compliance, model risk management, auditability, or regulated enterprise workflows.
• Experience designing human-in-the-loop workflows, approval systems, or agent control mechanisms.
• Experience at an early-stage company where senior engineers are expected to shape product and architecture.

Responsibilities

• Lead design and implementation of AI/ML systems that power autonomous financial-services workflows.
• Architect agentic systems involving LLMs, retrieval, embeddings, tool use, planning, classification, ranking, and structured reasoning.
• Build rigorous evaluation infrastructure for measuring agent quality, task completion, hallucination risk, accuracy, latency, and regressions.
• Translate customer and product needs into technical AI system designs that are reliable, auditable, and scalable.
• Own major AI/ML workstreams from exploration through production deployment.
• Partner closely with backend, product, and solutions teams to ensure AI capabilities are deeply integrated into the platform.
• Mentor engineers on AI system design, experimentation, evaluation, and productionization.
• Establish engineering standards for AI reliability, observability, safety, and maintainability.

Benefits

• Work on production agentic AI systems for complex, regulated customer environments.
• Join a high-ownership team where senior engineers directly shape product direction and technical culture.
• Help set the standard for reliable autonomous agents in financial services.