Top Artificial Intelligence Jobs in Nagoya

Mentor students in Nanodegree programs, provide project reviews and technical support, offering personalized feedback and responding to queries promptly.

Early-career software engineer role contributing backend/full-stack feature development, testing, CI/CD, and production releases. Collaborate on API/module design, system integration, and deployment. Support engineering of AI/LLM features (LLM APIs, basic RAG, embeddings/agents), maintain datasets/benchmarks, track performance, debug issues, and produce technical documentation.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Own end-to-end Instagram Reels production: ideation, scripting, editing, and delivery. Use AI tools to support ideation and production, test formats, optimize for retention, and stay on top of short-form video trends to grow international audiences.

As an AI Data Expert, review and annotate AI-generated outputs, ensuring cultural relevance and accuracy. Contribute to AI training with original content and detailed feedback while working flexibly as an independent contractor.

Design and implement backend AI systems centered on LLMs and agentic workflows. Build AI agent orchestration (model/tool calling, multi-step reasoning, state management, error handling), integrate models, RAG, and inference services, optimize for high concurrency (streaming responses, async scheduling, caching, cost control), and collaborate with product, frontend, algorithm, and platform teams to deliver scalable AI capabilities.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Designs and implements AI, automation, and analytics solutions for supply chain. Develops data models, governance, reporting, and advanced analytics; collaborates with process owners to enable data-driven decisions and trains/supports business users.

Develop AI-powered systems for supply chain workflows. Implement agentic AI features, build backend services, and support testing and validation for AI systems.

The Software Engineer in Test III will develop and execute automated tests, maintain testing tools, analyze defects, and ensure product testability within TraceLink's software solutions.

The Senior Software Engineer in Test builds and executes automated tests, develops testing tools, and collaborates on technical designs while ensuring system testability for the TraceLink platform.

The AI Solution Sales Specialist advises enterprise clients on leveraging AI for business transformation, guiding them from opportunity qualification to deal closure. This role involves driving the entire sales cycle, building business cases, and leading workshops with executives.

Partner with sales to design and demo agentic, predictive, and generative AI solutions; build MVP agentic applications; lead PoV engagements; define enterprise integration, security, governance, and deployment requirements; advise on data readiness and compliance; and provide cross-functional feedback to product and go-to-market teams to accelerate AI adoption and production readiness.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

Create high-impact AI-generated video and animated ad creatives from brief to final delivery. Use generative AI tools for ideation, moodboarding, prompt engineering, asset variation, and production polish. Collaborate with business and local market teams, present work to stakeholders, and optimize creative performance for marketing and paid ads.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Design, build, and deploy production AI agent workflows and LLM-powered systems. Integrate tools, APIs, databases, and internal services; improve agent quality, latency, safety, and cost. Collaborate with product and operations to translate business problems into practical AI solutions and contribute to backend services and evaluation/guardrail patterns.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Early-career software engineer in a fixed-term accelerator contributing to backend/full-stack feature development, testing, CI/CD, and deployments. Collaborate on API and system design, integrate and deploy AI/LLM capabilities (LLM APIs, RAG, embeddings, agents), build datasets/benchmarks, monitor performance, debug issues, and produce technical documentation.

Lead end-to-end execution of strategic AI and technology initiatives, driving Agile delivery across engineering, product, data, and infrastructure teams. Remove blockers, manage dependencies, align stakeholders, and accelerate organization-wide AI adoption while fostering a high-ownership, innovation-driven engineering culture.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.

Build internal AI developer productivity tools (coding assistants, retrieval systems, workflow automation). Develop LLM-powered apps for code generation, understanding, and test automation. Integrate AI across the SDLC, embed with teams to remove friction, experiment with prompt engineering, RAG, and AI agents, and evaluate emerging AI technologies.

Design, build, and maintain high-performance backend services and APIs using Java/Spring Boot. Develop and productionize recommendation algorithms and LLM systems, optimize LLM workloads (including on-prem), ensure scalability, reliability, and security, and collaborate across time zones with product and project teams to own end-to-end architecture.

Lead planning, design, delivery and promotion of a customer-service chatbot management platform. Use AI and big data to improve CS operations (corpus training, SOPs, assistant replies, summaries). Collaborate with engineering, UX, and CS teams. Monitor KPIs and user cases to drive product improvements.