The opportunity
Build, coach, and grow a team of Applied AI Engineers serving Mega accounts: hire strong technical builders, develop them through structured feedback and clear competency expectations, and create scalable onboarding for a customer-facing technical role.
What you'll do
Build, coach, and grow a team of Applied AI Engineers serving Mega accounts:: hire strong technical builders, develop them through structured feedback and clear competency expectations, and create scalable onboarding for a customer-facing technical role.
Staff engineers into account-aligned pods alongside Applied AI Architects,: balancing deep account continuity with flexibility to move expertise where the segment needs it most.
Set performance goals aligned with each Mega's technical account plan and the: segment's consumption objectives, and establish the metrics, reporting cadence, and dashboards that keep pod leads and cross-functional stakeholders informed on team health and impact.
Serve as a senior technical advisor to Mega product and engineering leaders: as they deploy production Claude workloads: guiding architecture design, evaluation strategy, and advanced prompting, agentic, and implementation patterns from discovery through deployment.
Lead hands-on co-build initiatives with Mega engineering teams, from: prototypes and pilots to production deployments, in support of each account's joint roadmap with Anthropic.
Help navigate the partner-customer duality: support both direct consumption and the distribution of Claude through Mega platforms and marketplaces, and exercise sound judgment about what we build together and share.
What they're looking for
- Act as a technical escalation point for your team's accounts, and partner: with pod leads and Mega Sales to sequence technical work for maximum customer value.
- Build shared assets across pods, including reference architectures, agentic: patterns, and eval frameworks, so that what one pod learns benefits every Mega account.
- Collaborate with Product and Research to surface Mega-driven requirements: with the right weight and context, advocating for high-impact product changes without becoming a feature-request pass-through.
- Champion scalable public and internal assets documenting the latest LLM: prompting, evaluation, agentic, and architecture techniques; contribute thought leadership through talks, blog posts, and white papers.
