Jobs at Sierra

Own the full lifecycle of sales plays, from intake and prioritization through development, launch, seller training, measurement, and retirement. Partner with Product Marketing, Product, Sales Leadership, and Sales Engineering to create messaging, demos, battlecards, objection handling, and proof points. Measure play adoption and business impact, report results, and adapt programs for regional teams.

Build and optimize recruiting processes, interview workflows, dashboards, and AI-enabled tooling. Manage and customize the Ashby ATS and related recruiting systems, identify operational bottlenecks, improve hiring practices, and support interviewer enablement through training and documentation. Partner with recruiters, hiring managers, and cross-functional stakeholders in a fast-paced technology environment.

Conduct an applied AI research project with mentorship, covering agent evaluation, reasoning, tool use, policy adherence, post-training, and multimodal or voice models. Design rigorous experiments, analyze proprietary text and audio datasets, develop benchmarks, write and submit research papers, and collaborate with engineers to translate findings into production improvements.

Manage the operating cadence for Product and Engineering incident response teams, including planning, sprint workflows, retrospectives, dashboards, and initiative tracking. Coordinate cross-functional initiatives across Product, Engineering, Legal, Security, and Operations. Build scalable execution frameworks, analyze operational data, identify friction points, and improve processes, alignment, and team outcomes.

Own the technical pre-sales process for enterprise financial services customers, partnering with sales teams to discover use cases, design and demonstrate AI agent solutions, lead architecture and technical reviews, and communicate business value. Build tailored working agents, support procurement and executive stakeholders, mentor sales engineers, contribute reusable assets, and remain involved through implementation, launch, and account expansion.

Own end-to-end technical programs for enterprise AI deployments in customer-owned cloud environments. Coordinate infrastructure, security, networking, provisioning, model access, and observability teams; manage milestones, dependencies, risks, escalations, and launch cadence. Translate technical requirements into actionable plans and improve Sierra’s deployment playbooks, tooling, and operating standards while establishing the infrastructure TPM function.

Provides strategic and administrative support to the General Counsel and Partnerships leaders by managing calendars, travel, meetings, correspondence, events, and confidential information. Coordinates meeting preparation and follow-up, builds relationships with internal and external stakeholders, negotiates travel-related contracts, and develops administrative systems for a growing startup. The role requires regular in-office work in San Francisco and occasional travel with executives.

Design, build, and operate multi-cloud infrastructure across AWS, GCP, and Azure using Terraform and Kubernetes. Standardize deployments, support multi-tenant and isolated customer environments, build security and compliance guardrails, improve release tooling, and operate FedRAMP infrastructure. Drive reliability through observability, incident response, root cause analysis, and postmortems while writing Go-based automation and partnering with BYOC teams.

Own end-to-end technical pre-sales for strategic enterprise accounts, including discovery, solution design, demonstrations, architecture and security reviews, technical proposals, and executive stakeholder engagement. Mentor Sales Engineers, establish strategic deal playbooks, support customer launches and expansion, and share account insights with Product leadership. The role requires experience selling complex AI or technical products, leading $1M+ deals, and partnering with enterprise architects, engineering, and security teams.

Own strategic enterprise technical sales for financial services accounts, from discovery and solution design through demos, architecture and security reviews, deal closure, launch, and expansion. Build trusted executive relationships, lead $1M+ sales processes, coordinate internal teams, mentor sales engineers, create strategic deal playbooks, and inform product roadmaps. Apply AI tools to prepare discoveries, prototypes, demos, and proposals while ensuring customer-facing accuracy.

Own the technical pre-sales process for enterprise customers, from discovery and solution design through demos, architecture reviews, proposals, and deal close. Build tailored AI agent prototypes, explain business and technical value, collaborate with CX, IT, security, procurement, and executives, and support account expansion after the sale. Mentor sales engineers, create reusable assets, and use AI tools to improve technical sales workflows.

Own the end-to-end technical pre-sales process for strategic enterprise accounts, including discovery, solution design, demos, architecture and security reviews, technical proposals, and customer presentations. Build executive and technical relationships, support launches and account expansion, mentor sales engineers, develop strategic-deal playbooks, coordinate internal teams, and communicate customer insights to Product leadership. The role requires selling complex AI products to customers with $1M+ deal sizes.

Partners with enterprise sales teams to win and expand financial services customers. Leads the technical pre-sales cycle, including discovery, solution scoping, business-value articulation, platform design, demonstrations, architecture reviews, prototypes, and technical proposals. Collaborates with Sales, Product, and Agent Engineering to improve customer solutions and scale successful industry motions.

Serve as the technical partner to enterprise sales teams, leading discovery, solution design, demonstrations, architecture reviews, prototypes, and technical proposals. Build tailored AI agent solutions, explain business value to technical and non-technical stakeholders, manage multiple concurrent deals, and collaborate with Sales, Product, and Agent Engineering to improve Sierra’s platform and go-to-market strategy.

Own the end-to-end technical presales process for enterprise customers, from discovery and solution design through tailored AI agent demos, architecture reviews, proposals, and deal close. Partner with sales, customer technical teams, executives, procurement, and security stakeholders. Support launches, expansions, and account growth after the sale, while mentoring newer sales engineers and developing reusable industry assets.

Own the technical pre-sales process for enterprise public-sector customers, partnering with sales teams to discover use cases, design and demo AI agent solutions, lead architecture reviews, and articulate business value. Build working prototypes, engage technical and executive stakeholders, support launches and account expansion, mentor sales engineers, and create reusable industry assets. The role requires strong enterprise sales engineering experience, relationship-building, technical communication, and effective use of AI tools.

Support and evolve global compensation programs through analysis, market benchmarking, compensation planning, offer optimization, stock plan administration, and scalable tools. Partner with Recruiting, Legal, People teams, and business leaders while maintaining compensation bands, equity frameworks, dashboards, and self-service experiences. Use AI and automation to improve workflows, data accuracy, operational efficiency, and compensation insights across international markets.

Design and lead global onboarding programs for Account Executives and Sales Engineers. Deliver role-specific training, certifications, workshops, and AI fluency education; establish ramp metrics; use AI to scale enablement and coaching; partner cross-functionally to maintain accurate content; recruit subject-matter experts; gather feedback; and continuously improve the program across regional teams.

Build scalable data foundations and personalization systems for AI agents. Responsibilities include real-time eventing, streaming and batch ETL, Iceberg lakehouse infrastructure, OLAP querying, orchestration, experimentation, long-term agent memory, customer data platform primitives, analytics products, and optimization loops. The role may focus on platform engineering or full-stack product engineering, including ML-powered personalization and data visualization.

Build enterprise platform capabilities for identity, access management, integrations, extensibility, scalability, security, compliance readiness, reliability, and operational excellence. Develop reliable and secure backend-leaning full-stack systems for complex customer environments and AI-powered enterprise SaaS products.