Top Artificial Intelligence Jobs in Osaka

Build end-to-end software features across frontend, backend, and AI components. Responsibilities include developing interfaces, APIs, backend services, data pipelines, automation workflows, and LLM-powered applications such as RAG systems and AI agents. The role involves testing, documentation, debugging, cross-functional collaboration, product iteration, and using AI coding tools to improve development speed and quality.

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。

Drive generative-AI adoption for sales and admin teams: analyze workflows, design Copilot prompts and Gemini chatbots, improve Microsoft 365 and knowledge systems, train staff, coordinate with IT and vendors, and measure impact to boost productivity and DX.

Customer- and partner-facing technical specialist driving Secure AI and Copilot adoption across Japan. Lead technical engagements, workshops, demos, and POCs for Microsoft Defender and Purview, enable partners, translate requirements into secure solutions, and support deployment readiness and scalable partner enablement.

Provide technical support for Wiz's cloud and AI security product: troubleshoot customer issues, escalate as needed, manage incidents, create scalable automation and solutions, update documentation, and participate in on-call rotations.

Lead product roadmap and execution for AI-driven on-chain monitoring tools, coordinate cross-functional teams, analyze market and customer feedback, deliver product features on schedule, and communicate with stakeholders to align expectations.

Own revenue and commercial relationships for AI and agentic workloads in Japan. Carry quota, build pipeline with enterprise accounts, lead complex multi-stakeholder deals, partner with solutions engineering and ecosystem, drive demand via workshops/POCs, and provide customer feedback to shape product and go-to-market strategy.

Lead and operate enterprise Azure and Microsoft 365 platforms, manage hybrid identity (Entra ID/AD), deliver and govern AI solutions (Azure OpenAI, Azure ML, Copilot), provide L2/3 support, secure and govern cloud resources, manage on‑prem infrastructure, and drive vendor, project, and stakeholder engagement to scale AI initiatives.

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.

Early-career TechOps role: build dashboards/alerts, script repetitive ticket steps, participate in RCAs, log user pain points and propose fixes, create a lightweight agent (e.g., Telegram bot) with reusable skills, optimize incident-management workflows, and write actionable runbooks to improve support-driven user experience.

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.

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.

Join as an early-career full stack engineer to build frontend and backend product features, integrate AI coding tools into development workflows, translate product requirements into implementations, and grow toward autonomous full stack delivery while improving cross-team processes.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

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.

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 research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

Develop and maintain scalable backend services and APIs, collaborate with frontend developers, and lead new features and infrastructure improvements.

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