GCP AI Jobs

View detail

Lead the team responsible for the AI/ML Stack infrastructure that bridges ML research and large-scale production, evolving the stack to meet scalability needs in ML training and inference workloads. Develop and execute the long-term vision and roadmap for the MLOps team to support ML development and deployment across business units, balancing short-term tactical deliveries and long-term architectural transformation. Manage and mentor a team of 6-7+ engineers, allocate resources strategically to support existing services and strategic initiatives. Collaborate across machine learning, data science, product engineering, and infrastructure teams to identify and address bottlenecks and facilitate deployment of new solutions. Architect compute and storage pipelines to manage large datasets without fragmentation or latency. Modernize the AI product inference stack to support significant growth in AI runs globally. Work with Site Reliability Engineering to establish comprehensive system observability metrics. Conduct build vs. buy assessments and technology stack refresh audits to benchmark and ensure best toolsets are in use.

View detail

As Jasper undergoes an agentic AI shift, the AI & IT Systems Engineer role involves ensuring the IT infrastructure is robust, secure, and fine-tuned for advanced AI workflows, spending 70-80% of time on AI enablement deployments. Responsibilities include modernizing and improving IT systems to support autonomous AI workflows, building scalable automation infrastructure to enhance efficiency and reduce manual tasks, and operationalizing AI initiatives using tools like Claude, ChatGPT, and Zapier to create intelligent, cross-platform workflows involving platforms like Google Workspace and Slack. The role also requires managing core IT systems such as Identity Providers and Mobile Device Management, streamlining identity and access operations using features like Okta Workflows, and providing cross-functional technical support across departments to implement AI enablement projects. Additionally, the engineer manages a broad SaaS ecosystem, including Google Workspace and Linear, and assists in developing training resources and playbooks to facilitate team adoption of new AI tools.

View detail

As an Associate Forward Deployed Engineer, the responsibilities include working alongside senior engineers and directly with customers, who are leading AI labs, to solve pressing technical challenges. The role involves supporting the design and deployment of solutions that impact customer workflows and model performance, working across the stack, shipping quickly, and iterating based on real-world feedback. Tasks include partnering with AI labs and internal teams to identify needs and gather requirements, supporting solution design, working on custom asks from customers to prototype and deploy tailored solutions, tackling complex technical problems with support from senior engineers, taking increasing ownership from concept through deployment, rapidly prototyping, testing, and iterating on tools in response to real-time feedback, contributing to architectural discussions, helping establish best practices for reliability, scalability, and security, and documenting solutions to create technical playbooks for repeatable and scalable deployment processes.

View detail

The Manager, AI Deployment Engineering for Health & Life Sciences is responsible for owning the strategy and operating model of the HLS AI Deployment Engineering team to ensure alignment with company objectives and customer needs. They hire, mentor, and develop a high-impact team of AI Deployment Engineers focused on production deployments in healthcare and life sciences. This role establishes operating mechanisms, delivery standards, and best practices tailored to regulated environments. They foster a culture of technical excellence, customer empathy, and responsible AI deployment, drive successful enterprise deployments, and oversee end-to-end implementation of generative AI applications in production. The manager guides customers through complex integration efforts spanning R&D, clinical development, regulatory affairs, medical affairs, and IT; develops scalable frameworks for secure, compliant AI adoption under regulations such as HIPAA, GxP, FDA, and EMA; ensures measurable impact through activation, adoption, and workflow transformation; collaborates closely with Sales, Account Directors, Solutions Architects, Product, Security, and Legal teams; serves as a trusted technical advisor to executive and senior technical stakeholders; and provides structured product feedback informed by deployment challenges and industry requirements.

View detail

The Senior Engineer on the internal tools team is responsible for building and maintaining internal platforms and tools used by various departments such as People, Finance, Ops, Sales, and Engineering. The role involves owning features end-to-end, including requirements gathering, architecture, implementation, testing, deployment, and monitoring. The engineer is expected to write clean, well-tested, production-grade code and build API-first integrations to connect multiple business systems like HRIS, CRM, finance platforms, and developer tools. Responsibilities include designing for reliability, performance, and scalability, eliminating data silos by creating clean data pipelines, and owning services in production with monitoring, alerting, incident response, and post-mortems. The role also involves building AI/LLM-powered features to automate internal workflows, moving prototypes to production, and staying updated on emerging AI technologies. Collaboration includes working directly with business stakeholders to translate pain points into technical solutions, mentoring junior engineers, conducting code and design reviews, influencing technical direction, proposing architectural improvements, and driving best practices across the team.

View detail

Work on building the next generation of agentic AI infrastructure including secure code execution environments, agent state management, model routing and orchestration, identity and authentication, and resource management for long-running agent workflows. Turn emerging ML research ideas into production-ready infrastructure by building core platform capabilities for execution, storage, and state management; prototype and evaluate new technologies; and partner with research teams to align infrastructure with future agent system needs.

View detail

Build and ship features for North, Cohere's AI workspace platform; develop autonomous agents that interact with sensitive enterprise data; experiment rapidly and with high quality to engage customers and deliver solutions that exceed expectations; work across the entire product lifecycle from conceptualization to production; lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout.

View detail

Define and drive the product roadmap for Distyl’s internal AI platform, including vertical products, ensuring support for both internal teams and enterprise deployments. Partner closely with platform engineers, forward-deployed engineers, AI researchers, and customers to translate real-world use cases into scalable platform capabilities. Identify opportunities to turn one-off customer solutions into reusable product features. Prioritize development of platform components such as AI model orchestration, agent frameworks, evaluation pipelines, developer tooling, and enterprise data integrations. Gather feedback from internal teams and enterprise clients to improve developer experience and system reliability. Define clear product requirements, success metrics, and technical specifications for platform capabilities. Ensure the platform enables fast, reliable, and secure AI deployments for enterprise customers. Collaborate with leadership to align platform investments with Distyl’s strategic goals.

View detail

The Chief Technology Officer is responsible for defining the long-term architecture for A1's AI systems, infrastructure, and developer platform, evaluating trade-offs between speed of iteration and long-term system design, and ensuring systems are designed for scalability, reliability, and long-term evolution. They guide key decisions across model integration, data pipelines, distributed systems, and product architecture. The CTO works with engineers to translate product direction into clear technical execution, helps structure engineering workstreams and maintain team alignment on priorities, maintains high engineering standards while encouraging shipping, and establishes engineering culture, development practices, and technical standards across the company. They build and scale a world-class engineering team across key talent hubs including China and the US, identify strong technical leaders, define hiring standards and interview processes, and ensure technical workstreams move forward smoothly across teams and locations. The CTO works closely with product, research, and leadership teams and helps resolve cross-team technical and execution challenges.

View detail

The Chief Technology Officer will define the long-term architecture for A1’s AI systems, infrastructure, and developer platform, evaluate trade-offs between speed of iteration and long-term system design, and ensure systems are designed for scalability, reliability, and long-term evolution. They will guide key decisions across model integration, data pipelines, distributed systems, and product architecture. The CTO will work with engineers to translate product direction into clear technical execution, help structure engineering workstreams and keep teams aligned on priorities, maintain high engineering standards while focusing on shipping, and establish engineering culture, development practices, and technical standards. Additionally, they will build and scale a world-class engineering team across key talent hubs including China and the US, identify strong technical leaders, define hiring standards and interview processes, work closely with product, research, and leadership teams, ensure technical workstreams move forward smoothly across teams and locations, and help resolve cross-team technical and execution challenges.