Sr​/Distinguished Architect, AI Systems & Agentic AI

Remote (US)

Our client is a fast-growing, AI-first enterprise software company. Its planning platform helps some of the world’s largest brands make faster, smarter decisions. It brings planning work that usually sits in separate silos onto one platform, which cuts waste and recovers value that large enterprises lose to inefficiency. The company is well funded, operates globally and has a strong record of growth.

The company is looking for an exceptional AI technologist to help define and build the next generation of AI across its platform and solutions. This is a deeply technical, senior individual-contributor role. You’ll work closely with the company’s AI and technology leadership and with teams across AI, product engineering, semantic systems, data and forward-deployed engineering (FDE). "Architect" is the company’s senior individual-contributor technical track.

Architects stay hands‑on: they design systems, build prototypes, write and review code, run experiments and work directly with engineering teams on hard technical problems. The company is looking for someone with deep, hands‑on experience across the evolution of AI, from traditional machine learning through deep learning and representation learning to foundation models, language models, agents and modern AI systems.

Make AI a deep technical capability across the whole company. That means advancing the company’s agentic foundation, applying the right AI methods to enterprise problems, and giving product teams, FDEs and partners the building blocks to create sophisticated AI capabilities quickly, safely and rigorously.

• Agentic AI Infrastructure:
  Work with AI leadership to advance the company’s core agentic platform. Design reusable building blocks for context orchestration, tool calling, structured outputs, persistent memory, multi‑agent composition, observability, sandboxed execution and human‑in‑the‑loop governance.
• Enterprise Knowledge Integration:
  Lead the integration of advanced AI models with the platform’s enterprise data and semantic layer. Design hybrid AI systems that pair generative models with structured, rule‑based domain logic, so decisions across complex data sets are precise, explainable and compliant with policy.
• Core ML & Predictive Intelligence:
  Push the platform’s AI capabilities beyond generative AI into time‑series forecasting, representation learning, embeddings, anomaly detection, probabilistic modeling and causal inference, so each enterprise problem gets the right method.
• Closed-Loop Decision Systems:
  Build learning mechanisms that use past forecasts, recommendations, human overrides and real operational outcomes to keep improving accuracy, agent policies and automated workflows.
• Evaluation & Rigor:
  Set up rigorous, enterprise‑grade evaluation frameworks for AI and agent performance. Go beyond demos by benchmarking accuracy, grounding, constraint adherence, failure handling, reproducibility and real business ROI.
• Platform Leverage & Abstraction:
  Create high‑leverage abstractions, shared libraries and architectural patterns that let hundreds of product engineers, field engineers and partner teams build safe, high‑performing AI solutions quickly.
• AI‑Native Engineering Practice:
  Champion modern AI‑assisted development and prototyping tools to speed up engineering across the codebase, while keeping close technical oversight of generated code, system logic and experimental conclusions.

• Experience:
  
  15+ years of deep software engineering experience, with a proven record of designing, building and scaling advanced enterprise software platforms.
• Education:
  
  A bachelor’s degree in Computer…