Senior Forward Deployed Engineer

Climb is a Data and AI consultancy that partners with enterprises to design, build, and operationalize modern data platforms and production AI systems. As a Databricks partner, we go deep on lakehouse architecture, machine learning, and applied AI, with a bias toward production over proof of concept. Our team brings deep technical expertise and a builder's mindset to every engagement, and we measure our work not just by what ships, but by the business impact it drives., 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., * 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., * Outcomes, not hours. We sell and deliver against business results. Advancement is tied to delivery performance and account impact, not utilization targets.
• Senior team, no body-shop drag. Small pods of A-players, heavy internal AI leverage, and no bloated middle layers between you and the work.
• IP that compounds. Every engagement feeds reusable accelerators, patterns, and points of view back into the practice.
• Autonomy with a bench. Minimal oversight in the field, a strong senior technical bench behind you when the problem warrants it.

• 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., * 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.

Pulled from the full job description

• Paid time off
• Vision insurance
• Dental insurance, * 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

This role is designed for engineers who are ready to own complete workstreams today and are growing toward whole-system architecture and engagement leadership. * You naturally own an entire workstream and recognize delivery risks, organizational friction, and expansion opportunities before they become visible to everyone else. * You bring expansion signals forward without being asked. * You'd rather ship something maintainable than demo something clever.