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Forward Deployed Engineer

Posted An Hour Ago
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Hybrid
Denver, CO, USA
145K-200K Annually
Senior level
Hybrid
Denver, CO, USA
145K-200K Annually
Senior level
Own end-to-end customer deployments of AI and edge platforms across hardware, networking, sensors, data systems, and applications. Integrate customer OT/IT environments, diagnose cross-stack production issues, build deployment tooling, and translate field learnings into repeatable patterns and product improvements. The role requires strong engineering judgment, customer collaboration, autonomy, and 25–50% travel.
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Forward Deployed Engineer (FDE)

Hybrid — Denver, CO
Full-time

The Opportunity

Our client is seeking a Forward Deployed Engineer (FDE) to accelerate the application of AI in real-world environments by embedding with customers and partners to deliver high-impact deployments that drive measurable value.

In this role, you will own end-to-end delivery of customer outcomes using advanced AI and edge technologies—working across hardware, networking, sensors, data systems, and AI. You will integrate deeply into customer environments to compress adoption cycles, iterate based on real needs, and capture product insights that improve future deployments.

This role operates at the edge of the platform rather than inside its core. You will have significant ownership over field deployment and configuration decisions within established execution and release processes.

This is a hands-on, high-ownership role with 25–50% travel for someone who thrives in fast-moving environments and wants to build and deploy the infrastructure that enables real-world AI.

What You’ll Do
  • Own the design, deployment, and iteration of customer solutions from initial problem definition through production rollout and expansion

  • Deliver measurable outcomes by traveling to customer sites 25–50% of the time and working closely with customer and partner teams

  • Deploy and operate the platform in real environments across edge hardware, networking, connectivity, sensors, data flows, and AI inference

  • Build integrations and tooling connecting customer OT/IT systems, data sources, and workflows into production applications

  • Diagnose issues across the full stack (hardware → network → data → application → AI) and resolve production challenges quickly

  • Capture deployment learnings and translate them into repeatable playbooks, scalable patterns, and product feedback

  • Leverage AI tools to accelerate drafts, implementations, and artifacts while applying strong engineering judgment

  • Communicate clearly with technical and non-technical stakeholders and lead working sessions that drive execution

What Success Looks Like

In your first 3 months, you will have:

  • Taken ownership of at least one customer deployment and delivered measurable customer value

  • Built strong context on customer constraints and made sound cross-system trade-offs

  • Earned trust through autonomy, responsiveness, and high-quality execution

In your first year, you will be:

  • Independently owning multiple deployments or a strategic account end-to-end

  • Creating repeatable deployment patterns that reduce delivery friction and improve speed-to-value

  • Feeding continuous product improvements back to Engineering based on real-world learnings

Who You Are
  • 5+ years building and operating production software or systems, ideally in customer-facing or delivery roles

  • Experience working across infrastructure, networking, security, data systems, and/or production AI

    • Examples: Linux, Docker/Kubernetes, REST/gRPC APIs, observability tooling

  • Strong engineering fundamentals with clean implementations and thoughtful system design

    • Languages such as Python and/or Go; shell scripting

  • Comfortable working in ambiguity and making pragmatic trade-offs under real constraints

  • Clear communicator and strong cross-functional collaborator

  • Ownership mindset focused on delivery, adoption, and customer value

Unique Valued Experiences
  • Delivering complex deployments end-to-end and turning one-off wins into repeatable patterns

  • Hands-on experience with edge or hybrid systems (hardware, networking, connectivity, containerized environments)

    • Examples: VPNs, TLS, firewalls, LTE/5G/Wi-Fi, Kubernetes

  • Deep experience diagnosing cross-stack production issues (logs, metrics, traces, packet capture, performance profiling)

  • Production experience applying modern AI systems (LLMs, agents, inference) in real workflows

  • Experience embedding with customer and partner engineering teams to drive measurable outcomes

Compensation & Benefits
  • Base salary range: $145,000–$200,000 (based on location and experience)

  • Meaningful equity participation

  • Comprehensive benefits package, which may include medical, dental, vision, retirement plan with company match, flexible PTO, parental leave, commuter benefits, and relocation or visa support where applicable

About the Client

Our client is focused on deploying AI in real-world environments, helping organizations unlock meaningful productivity gains at the intersection of infrastructure, security, networking, and AI. Their teams operate in highly distributed, performance-critical environments where reliability and scalability are essential.

They maintain a strongly AI-native culture, leveraging AI daily to accelerate design, testing, deployment, and operations of complex systems. This is an opportunity to help shape how AI is applied in production environments at global scale.

Our client is an equal opportunity employer committed to building an inclusive and merit-based organization.

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