Senior Forward Deployed Engineer

Role Description

Senior Forward Deployed Engineers own complete workstreams within Climb's client engagements. You partner closely with the engagement's Forward Deployed Architect or AI Lead to turn ambiguous business problems into production systems, taking your workstream from discovery and design through implementation, deployment, and handoff.

At Climb, seniority means owning outcomes, not stepping away from the keyboard. You are the technical owner for your workstream: making design decisions within its scope, driving delivery, and collaborating with clients and teammates to keep the work moving. While the Architect or AI Lead owns the overall engagement, you influence technical direction through strong execution, sound engineering judgment, and early identification of delivery risks and opportunities.

Our engagements focus on building production data platforms, AI applications, intelligent agents, and modern analytics systems, most often on Databricks, but always using the technologies that best fit the client's environment and business goals.

Key Responsibilities

• Own the workstreams and components you are responsible for, from design through production, inside the client's environment.
• Participate in discovery, architecture reviews, and stakeholder interviews on your area of the engagement; turn vague problems into scoped, deliverable work.
• Make the build and design decisions appropriate to the client's environment and constraints on the work you own, and stand behind them.
• Build the system: production data pipelines, LLM applications, agents, and workflow automations that meet spec and hold up under real load.
• Manage scope actively on your workstreams: surface risk and creep before it becomes a problem, not after.
• Transfer capability that lasts: documented, runnable, maintainable software that works after you leave.
• Build trusted relationships with client stakeholders while supporting the Architect or AI Lead in overall account ownership.
• Contribute reusable patterns and lessons learned that improve future delivery.

Qualifications

• 5+ years of engineering or technical delivery experience, with meaningful time in embedded or client-facing contexts.
• Proven delivery ownership: clear evidence you've taken client-facing work from scoping through production with limited supervision.
• Hands-on depth in one or more of: LLM application development, cloud-native architecture (AWS, Azure, or GCP), backend systems at scale, or production data engineering.
• Demonstrated ability to make independent technical decisions and own your own delivery quality inside a client environment.
• Strong communicator: technically precise with engineers, clear and confident with VP- and C-level leadership, and able to adjust depth without losing accuracy.
• High tolerance for ambiguity; consistently delivers value before every requirement is defined.

Preferred Qualifications

• Experience building production AI systems: RAG pipelines, agents, fine-tuned models, or LLM-native applications.
• Hands-on experience with Databricks (Delta Lake, Workflows, Unity Catalog, Mosaic AI) is a strong plus.
• Background in a consulting firm, systems integrator, or professional services environment.
• Familiarity with SOW-based, outcome-priced delivery and active scope management.
• Note on certification: Databricks experience is valued but not required at hire. Both Databricks and Anthropic certification are expected to be obtained post-hire.

Benefits

• Competitive base salary with performance-based bonuses
• MacBook Pro and swag kit so you can do your best work
• Comprehensive health, dental, and vision insurance
• Generous holidays, flexible PTO, and remote-first work environment
• Professional development budget including Databricks and cloud certifications
• Spot bonuses for relevant certifications
• Conference attendance and thought leadership opportunities
• Collaborative, low-ego culture with direct access to leadership
• Opportunity to shape a growing practice from the ground floor