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ai&

Builds enterprise AI platform with governance

Member of Technical Staff - Applied & Agentic AI

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • Experience building production agentic systems, including orchestration, tool use, memory, multi-step planning, and reliability at scale.
  • Practical experience working with models through prompting, chaining, evaluation, and iteration.
  • Experience designing and maintaining evaluation pipelines for AI systems that reflect user needs.
  • Ability to reduce platform complexity, create clean interfaces, and establish easy-to-follow development patterns.
  • Comfort building across backend services and application programming interfaces, with the ability to own workflows end to end.
  • Strong command of Python.
  • Familiarity with agentic frameworks such as LangGraph or AutoGen, evaluation tooling, and inference application programming interfaces.

Responsibilities

  • Build and maintain agentic frameworks for deploying agents on ai& infrastructure, integrating and extending open-source solutions such as LangGraph, AutoGen, and MCP to create production-ready tools for internal teams and customers.
  • Build customer-facing interfaces, workflows, and abstractions to make agent deployment straightforward.
  • Design and build custom agentic workflows on the ai& inference product that demonstrate its capabilities and support customer deployments.
  • Own the evaluation pipeline for inference models; design evaluations that reflect real-world usage, detect regressions, and support decisions about model publishing and deployment.
  • Build agentic tools and workflows used by internal engineering teams.

About the Company

ai&

Builds enterprise AI platform with governance

AI&D builds an enterprise AI platform and offers end-to-end AI services to help organizations adopt, govern, and deploy AI across operations, covering strategy, data governance, use-case discovery, and production implementation. It aligns AI with business goals through maturity assessments, data strategy, governance, readiness checks, proofs of concept, and hackathons, and it develops frontier models in language, video, and multimodal domains with continual learning to improve security and performance while integrating with client systems. It differentiates itself by offering a unified global platform across multiple modalities, with a strong emphasis on continual learning, data governance, and hands-on enablement tailored to enterprise environments rather than only building models. Its goal is to help enterprises transform operations and create measurable business value by embedding AI into core processes with productive, scalable, and secure AI-enabled systems.

Company size
11-50
Company stage
Seed
Total funding
$57.8M
Headquarters
Yokohama, Japan
Founded
2026

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