Technical Account Manager
Remote • San Francisco Office (Fremont St) • FullTime
Posted 12d ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Lambda, a leader in AI cloud infrastructure, is seeking a Technical Account Manager to own the technical health of post-sales relationships for their public cloud accounts. This hands-on role involves understanding customer AI use cases, leading joint POC sessions, designing and defending architectures, and owning SLA and reliability engineering. You will build tooling to make accounts measurable, direct technical escalations, and serve as the technical voice of the customer within Lambda. The ideal candidate will have a deep understanding of GPU infrastructure and AI/ML workloads, with a proven ability to lead structured technical engagements and communicate complex technical content effectively.
Responsibilities
- Own the technical health of assigned accounts from handoff through steady state, expansion, and renewal.
- Understand customer AI use cases (training, fine-tuning, inference) and map their stacks.
- Lead joint customer Proof of Concept (POC) sessions with defined success criteria.
- Produce and defend reference architectures for compute, networking, storage, and scheduler integration.
- Build and own the methodology for uptime, downtime, and credit calculation, validating SLA breach events.
- Build and drive adoption of technical data surfaces for customer health, including dashboards and telemetry.
- Serve as the technical lead during high-severity incidents, driving root cause analysis and coordinating resolution.
- Manage a feature-request pipeline into product and audit the platform hands-on.
- Track the market technology landscape, including GPU roadmaps and competing clouds, to inform recommendations.
Requirements
- 5+ years in technical account management, solutions engineering/architecture, ML engineering, technical program/product management, or infrastructure engineering with customer-facing scope in cloud, HPC, or AI infrastructure.
- Hands-on fluency with GPU infrastructure, including provisioning, benchmarking, and debugging compute, networking, storage, and schedulers.
- Working command of AI/ML workloads (training, fine-tuning, inference) to map customer stacks and lead technical conversations.
- Track record of leading structured technical engagements like POCs, architecture designs, or escalations.
- Proficiency in scripting, SQL, and dashboarding, with experience turning operational data into tools.
- Executive-grade communication skills for deeply technical content, both written and verbal.
- Comfort with ambiguity and a track record of building processes and tools.