Forward Deployed Team Lead

C3 AI•Redwood City, CA

9h•$155,000 - $197,000

About The Position

C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI Forward Deployed Team Leads are senior technical leads who own a commercial or enterprise customer end-to-end. You’ll combine strong technical architecture, hands-on coding, product ownership, project management, and stakeholder communication—embedding directly with customers to take our product from “design” to “in production.” You’ll own one account at a time: scope the workflow with business and technical stakeholders, design the architecture, write the code that closes the gaps, and drive the deployment through to measurable business value.

Requirements

BS/MS in Computer Science, Software Engineering, Engineering, or equivalent practical experience.
6+ years shipping production software, with 2+ years as a tech lead or senior individual contributor owning delivery end-to-end.
Strong proficiency in Python, TypeScript/JavaScript, Java, Go, or C++.
Demonstrated ownership of systems taken from zero to production in a commercial or enterprise context.
Bring deep expertise in at least one vertical (financial services, healthcare, energy, manufacturing, or defense) to accelerate time-to-value and credibility with customer stakeholders.
Experience working directly with business and technical stakeholders at mid-market or enterprise accounts—comfortable in both exec-level conversations and deep technical design sessions.
Familiarity with enterprise data environments: cloud data warehouses (Snowflake, Databricks, BigQuery, Redshift), REST/GraphQL APIs, and common ERP or CRM platforms.
Comfort with modern deployment practices: CI/CD, containerization (Docker/Kubernetes), cloud-native services, and infrastructure-as-code (Terraform or equivalent).

Nice To Haves

Prior experience as a tech lead or staff engineer at a SaaS or enterprise software vendor with a forward-deployed or professional services motion.
Experience with AI/ML platform deployments or data-heavy enterprise applications at scale.
Familiarity with major cloud environments: AWS, Azure, or GCP, including managed ML/AI services.
Experience in regulated industries (healthcare/life sciences, manufacturing, energy) where compliance and change management are part of the delivery.
Proven ability to turn a messy, ambiguous customer problem into a clean, repeatable deployment pattern.

Responsibilities

Technical architecture. Own data flow, integration topology, identity model, and deployment architecture across the customer’s infrastructure.
Hands-on coding. Write production code yourself—backend services, data pipelines, APIs, integrations.
Product ownership. Own the deployment’s roadmap. Execute on the statement of work. Decide what’s in scope, what’s a one-off, and what should become product.
Project management. Own the plan, milestones, risks, and dependencies. When something slips, know first and flag first.
Stakeholder communication. Run customer working sessions, brief executive sponsors, and write clean status updates that senior stakeholders will actually read.
Ship into production. Deploy from dev through UAT into production—including integration with customer data warehouses, ERP/CRM systems, and cloud environments (AWS, Azure, GCP).
Enterprise readiness. Ensure the platform is configured, secured, and monitored to meet enterprise security and compliance requirements (SOC 2, ISO 27001, data residency, etc.).
Bridge field back to product. Push field learnings into the core platform so the next deployment is faster.
Account growth and development. Partner with Sales to identify expansion opportunities within the account—surfacing new use cases, supporting renewal conversations, and ensuring successful deployments convert to long-term customer relationships.