AI/ML Engineering Jobs

Strategic Account Executive role focused on driving enterprise revenue within cybersecurity accounts leveraging Claude and agentic AI systems. Requires deep technical understanding of AI deployments, complex B2B sales cycles, and ability to navigate multiple stakeholders from engineering to C-suite in building next-generation AI-powered security products.

This is a Strategic Account Executive role focused on driving AI adoption in Canadian financial institutions rather than an AI/ML technical position. The role requires enterprise sales expertise, deep financial services knowledge, and the ability to navigate complex regulatory environments and multi-stakeholder negotiations to close large deals.

This is a go-to-market sales role focused on enterprise adoption of Claude AI within asset and wealth management firms, not a technical AI/ML position. The role requires deep understanding of financial services, ability to navigate complex organizational structures, and expertise in consultative enterprise sales—responsibilities are oriented toward business development and customer strategy rather than AI research or engineering.

Lead startup partnerships and Claude adoption across France and Southern Europe by building strategic relationships with VCs, accelerators, and AI-native startups. Design GTM programs, negotiate partnership terms, and use data analytics to drive growth and measure program impact. This is a 0-to-1 builder role requiring both business acumen and technical depth to advise founders.

Staff-level security engineering role at Anthropic focused on designing and building complex security systems to protect AI infrastructure, model weights, and training data. The position involves leading multiple security domains including identity/secrets management, developer security, and infrastructure security while mentoring engineers and shaping security culture across the organization.

Anthropic is seeking a Staff+ Software Engineer to design and optimize foundational platform infrastructure that accelerates product development across the organization. You'll architect critical systems including dev environments, CI/CD pipelines, service infrastructure, and multicloud operations while partnering with research and product teams to scale reliable systems for hundreds of thousands of users.

This Staff+ role leads Anthropic's observability infrastructure, owning monitoring and telemetry systems that scale across massive GPU/TPU clusters. The engineer will design high-throughput ingest pipelines, cost-efficient storage solutions, and AI-assisted diagnostic tools to help teams detect and resolve issues faster. The position requires 10+ years of industry experience and significant expertise in distributed systems, observability platforms, and infrastructure engineering.

Staff-level infrastructure engineer needed to build and optimize the critical inference systems serving Claude to millions of users globally. The role requires expertise in distributed systems, performance optimization, and intelligent request routing across diverse AI accelerators and cloud platforms. Success demands balancing compute efficiency for scale with enabling breakthrough AI research through high-performance inference infrastructure.

This Staff-level role focuses on building and maintaining critical inference infrastructure that serves Claude to millions of users globally. You'll optimize compute efficiency and enable AI research by architecting scalable, high-performance distributed systems for LLM serving across multiple cloud platforms and AI accelerators.

Anthropic seeks a Staff+ Full-stack Software Engineer to lead product engineering efforts across Claude.ai, APIs, and enterprise deployments. You'll own end-to-end technical quality and developer experience, building tools and platforms that enable developers to leverage LLM capabilities at scale. This role requires strong full-stack fundamentals, product-oriented thinking, and expertise in building reliable systems for millions of users globally.

Staff+ role leading Anthropic's Developer Productivity infrastructure team, responsible for owning end-to-end engineering systems that support model training, safety experiments, and Claude deployment at scale. Requires 10+ years of large-scale infrastructure experience and 3+ years of technical leadership, with focus on build systems, CI/CD pipelines, and developer acceleration tooling integrated with AI capabilities.

Staff-level data infrastructure engineer role at Anthropic focused on designing and operating secure, scalable data systems across the organization. Responsibilities span data governance, financial pipeline reliability, cloud storage architecture, and platform tooling optimization, requiring deep expertise in distributed systems and cloud infrastructure.

Anthropic seeks a Staff+ Software Engineer to architect and scale database infrastructure supporting millions of Claude users and research workloads across multiple cloud providers. This role requires 10+ years of database systems experience with 3+ years leading complex projects, focusing on distributed OLTP systems, multi-cloud deployment strategies, and build/buy decisions at massive scale.

This Staff+ role focuses on building the infrastructure layer for Claude's agentic capabilities, including sandboxed execution environments, state management for long-running tasks, and secure delegation frameworks. The position requires 10+ years of distributed systems experience at hyper-scale with deep expertise in cloud-native infrastructure, containerization, and security-focused system design.

Build and own mission-critical billing infrastructure at Anthropic that converts product usage into revenue across all platforms. Design end-to-end billing capabilities with an obsessive focus on correctness, reconciliation, and audit compliance while managing complex integrations with third-party payment and tax platforms. Lead architectural decisions for pricing primitives, payment flows, and revenue data foundations that scale with the business and support cross-functional teams.

Staff+ backend engineer role at Anthropic focused on building and scaling systems that power Claude API, Claude.ai, and Claude Code for hundreds of thousands of users. The role spans multiple specialized teams (API Core, API Capabilities, API Knowledge) requiring independent project ownership, cross-functional leadership with research and product teams, and hands-on technical execution. Strong emphasis on reliability, performance optimization, feature productionization, and architectural decision-making for frontier AI systems.

This Staff-level role focuses on ensuring the reliability and resilience of Anthropic's Claude LLM serving infrastructure across the complete token path. The ideal candidate brings strong distributed systems and SRE expertise to design monitoring systems, establish SLOs, implement high-availability infrastructure, and lead incident response for critical AI services. Success requires both deep technical infrastructure knowledge and exceptional ability to collaborate across teams to solve emergent reliability challenges at scale.

This Staff-level role focuses on ensuring Claude's reliability across serving infrastructure, from SDKs through APIs to accelerators. The engineer will design SLOs, build monitoring systems, manage incidents, and partner across teams to maintain high availability for one of Anthropic's most critical services.

Staff-level infrastructure engineer role focused on building and scaling the inference systems that serve Claude to millions of users. The role requires expertise in distributed systems, LLM inference optimization, and cloud infrastructure across multiple accelerator platforms, with equal emphasis on maximizing compute efficiency and enabling cutting-edge AI research.

Build and operate production data pipelines and observability systems for Anthropic's large-scale accelerator fleet across multiple cloud environments. Own telemetry ingestion, normalization, fleet health monitoring, and utilization optimization at meaningful scale. Requires deep expertise in data engineering, Kubernetes infrastructure, and systems engineering with ability to operate autonomously in a high-ambiguity environment.