Top Artificial Intelligence Jobs in Tokyo

Act as product specialist for CalypsoAI within F5's enterprise GTM, partnering with account teams to drive and close complex AI-security sales. Engage senior security and technology stakeholders, deliver tailored demos and proof-of-value, manage pipeline and forecasting, and feed customer insights into product and GTM strategy.

Develop and improve Vision-Language models for robotics, build training pipelines, conduct error analyses, and establish infrastructure for model deployment.

Design polished, user-centric mobile and web interfaces for BJAK's AI and financial products. Create wireframes, flows, prototypes and high-fidelity UI. Maintain and evolve the design system, ensure accessibility and responsiveness, collaborate with PMs and engineers for pixel-perfect implementation, and iterate using user feedback and analytics.

Embed with customers to discover and prioritize business problems, design and implement LLM/agent-based AI solutions, deploy in enterprise environments, measure outcomes scientifically, and act as liaison to product teams. Requires hands-on engineering, prompt engineering, agent and eval framework development, and periodic onsite collaboration (20–50%).

Design, train, and deploy generative AI and predictive models (including RAG) on Azure. Integrate ADLS/Synapse data, build serverless connectors with Azure Functions, enable low-latency retrieval via Azure AI Search, and implement MLOps, CI/CD, monitoring, and lifecycle management for production AI solutions.

Lead design, development, and delivery of cloud-native, microservice-based software products. Drive DevSecOps/CI-CD practices, API/system integration, quality assurance, customer-facing solution design, project leadership, and adoption of AI/IoT/digital-twin technologies.

Design, architect, and implement hybrid and cloud solutions (Azure) while hands-on deploying and fine-tuning generative and pre-trained AI models. Lead teams, govern technical delivery, perform prompt engineering, use Azure OpenAI, Form Recognizer, Cognitive Search, and vector databases, and develop upskilling sessions. Require Python/PySpark experience and stakeholder management.

Design, build, and deploy scalable Generative AI and predictive models (including RAG) on Azure. Integrate models with data pipelines in Azure Data Lake/Synapse, implement serverless orchestration, apply MLOps, and enable real-time and batch inference while collaborating with engineers and business stakeholders.

Lead Azure cloud and AI sales for major trading/retail customers: engage CxO stakeholders, design and drive migration, modernization, data platform and AI application solutions, orchestrate partners and internal teams, manage pipeline and forecasting using AI-driven analytics, and promote Azure adoption and consumption.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable customer-facing systems. Drive architecture, code quality, observability, testing, incident response, and engineering culture while coaching engineers and delivering product outcomes from idea to production.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable customer-facing products. Own architecture, delivery, code quality, observability, incident response, and engineer development while partnering with product, design, mobile, backend and AI teams to deliver business outcomes.

Lead technical design and delivery of scalable backend, frontend, API, database and cloud systems. Stay hands-on coding, review and mentor engineers, drive architecture and reliability, own production incidents, and partner with product and AI teams to ship high-quality features.

Lead technical design and delivery of scalable, reliable payment and AI-integrated systems. Remain hands-on coding, review code, mentor engineers, make architecture decisions, improve tooling, and own production reliability and incident resolution.

The Customer Technology Advisor role focuses on leveraging technical expertise in Application Data and AI to deliver solutions and support sales activities, enhancing customer relationships through consultative selling methods.

Lead technical design and execution of major products, remaining hands-on to code, review, debug and operate production systems. Make architecture decisions across backend, frontend, APIs, databases and cloud, mentor engineers, improve tooling and reliability, and drive initiatives from idea to production.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable customer-facing payment systems. Drive architecture, code quality, observability, incident response, and engineering processes while coaching engineers, prioritizing product outcomes, and delivering features from idea to production.

Lead technical design and execution of major products across backend, frontend, APIs, databases and cloud. Hands-on coding, code review, debugging and production ownership. Make architecture decisions, mentor engineers, improve tooling, and drive reliability, testing, and observability. Work cross-functionally to deliver high-quality AI-enabled email product features from idea to production.

Lead and manage a cross-functional engineering team to deliver reliable, scalable, customer-facing products. Own architecture, delivery, code quality, observability, incident response, and engineer development while collaborating with product, design, mobile, backend and AI teams to turn ambiguous problems into production systems.

Participate in a 14-day remote notification-sorting pilot using a Google Pixel 9+ device. Interact naturally with apps that generate notifications, complete daily 10–15 minute tasks, submit feedback/check-ins, and report issues. Must follow instructions, maintain confidentiality via Upwork, and provide documentation as requested.

Manage the AI Tooling engineering team, define vision for AI technologies, ensure feature delivery, improve engineering excellence, and handle technical challenges.

Lead AI workforce go-to-market (GTM) activation in Japan by aligning sales, marketing, partners, and operations to drive adoption and revenue. Build execution plans for solution plays, champion customer and partner needs, enable sellers with tools and rhythms, and use data-driven insights to optimize pipeline and demand generation. Act as cross-functional thought leader to remove roadblocks and scale field impact.

Conduct research and build generative and agentic AI systems (LLMs, VLMs, agents); advance post-training techniques (SFT, RLHF, RL), improve model performance and scalability, design evaluations and benchmarks, and collaborate to deploy research into production and publish findings.

Research, train, evaluate, and optimize deep learning computer vision models for infrastructure inspection. Perform data preprocessing, experimentation, post-processing, and assist with model integration and deployment. Collaborate with an experienced engineer, present results, and work within an international team.

Operate in the CEO Office to translate CEO priorities into execution across product, hiring, licensing, partnerships and market launches; track OKRs and decisions; prepare briefs and action trackers; coordinate cross-functional teams and close execution gaps on urgent business problems.

Lead enterprise AI adoption using Microsoft 365 Copilot and Azure AI. Define AI business vision and KPIs, design transformation roadmaps, measure ROI, drive end-to-end project delivery, advise executives, manage risks, and contribute IP and community knowledge sharing to scale AI solutions.