Top Artificial Intelligence Jobs in Osaka

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

Lead a team designing, delivering, and scaling AI and automation solutions across Azure and Microsoft 365. Manage hybrid identity, Azure operations, M365 administration, security/compliance, on-prem servers, vendor relations, and AI strategy (Copilot, OpenAI, Cognitive Services). Oversee governance, POCs, and enterprise adoption while providing L2/3 support and project delivery.

Lead and execute AI-driven consumer product initiatives for search, recommendations, personalization, and conversational experiences. Collaborate with engineering, design, data, and business teams to define requirements, use data and user feedback to refine products, and deliver improvements within the contract period.

Lead design and delivery of cloud-native, event-driven platforms and applications. Drive full lifecycle development, champion engineering best practices, implement production-ready solutions, and build AI/LLM capabilities like RAG, embeddings, and model CI/CD across multi-cloud environments.

The Forward Deployment Engineer will architect multi-agent systems, manage LLM adaptation strategies, build RPA task bots, and lead stakeholder discovery workshops.

As a Forward Deployed Engineer, you'll develop solutions integrating AI with customer workflows, build data insights, and guide technical adoption in client environments.

Build and scale a full-stack Next.js application tracking PRs, CI health, test parity, and benchmarks across AI accelerator open-source projects. Integrate GitHub APIs and webhooks, design PR/metrics schemas, visualize results, and produce technical digests and reports on cross-accelerator parity and performance trends.

The role requires driving AI-driven solutions within customer teams, ensuring adoption of OutSystems capabilities, and delivering intelligent solutions while embedded in complex environments.

Design and build internal AI productivity tools and LLM-powered applications to augment developer workflows. Integrate AI into the software development lifecycle, apply techniques like prompt engineering, RAG, and agents, partner with engineering teams to identify bottlenecks, and continuously evaluate emerging AI technologies to improve internal platforms and engineering efficiency.

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.

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.

Lead strategy, design, deployment, and scaling of agentic AI, generative AI, predictive analytics, and MLOps across commercial, medical, and enabling functions. Build governance, evaluation, and production standards; transition PoCs to scalable AI capabilities; hire and lead AI teams and drive business adoption in regulated environments.

Lead design and delivery of AI-powered system transformations for enterprise clients across the full lifecycle: requirements, design, development, testing, migration, project management, and operations. Develop and deploy generative AI (LLM/RAG/agent) solutions, collaborate with cross-functional and global teams, and improve internal system integration and operational practices.

エンタープライズ向けに生成AIやクラウドを活用した業務変革を推進するポジション。要件定義〜設計・開発・テスト・移行・運用設計までのシステムライフサイクルとプロジェクト管理、社内外チームやグローバル連携での価値創出を担当します。