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Dexterity

AI-powered robots autonomously load trailers

Forward Deployed Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeRedwood City, CA, USA$130k - $170k /yr

About the Job

Requirements

  • A Bachelor of Science or Master of Science in Computer Science, Robotics, or a related discipline, or relevant experience.
  • Proficiency in Python or C++, with experience implementing a large project or product feature.
  • Willingness to work across the full breadth of the robot stack, from sensors to software.
  • Ability to instrument, query, and visualize telemetry to inform decisions.
  • Familiarity with support tools and observability platforms such as Grafana, Kibana, Foxglove, and ArgoCD.
  • Strong analytical and debugging skills, including experience parsing logs and telemetry data.
  • Ability to translate technical findings into customer-friendly language and clear bug reports.
  • Willingness to take ownership in ambiguous environments.
  • Sense of urgency in production environments and willingness to own tickets through closure.
  • A bachelor's degree in an engineering discipline such as Mechanical, Electrical, Industrial, or Robotics, or Computer Science, with demonstrable coding skills and a solid grounding in computer-science fundamentals; equivalent practical experience is welcome.
  • At least 2 years in a SaaS, DevOps, Site Reliability, or Application Support role handling customer-facing production systems.
  • Comfort working extended hours and on-site or on-call rotations for high-severity incidents.

Responsibilities

  • Drive new solution operations in the field, resolve early issues, meet customer key performance indicators, and prepare solutions to scale after pilots.
  • Drive fixes and improvements based on field experience, using methodologies that provide traceability, change management, and prevention of repeat occurrences.
  • Release solutions that are ready to scale and meet operator expectations for ease of use, uptime, and operator-to-robot ratio.
  • Serve as the named technical point of contact for one or more strategic sites.
  • Develop integrations, robotic skills, and capabilities to meet customer challenges, and incorporate field learning into core platform capabilities.
  • Deliver actionable bug reports and reproducible cases to accelerate root-cause analysis.
  • Develop tooling and documentation, guide application services teams at pilot and production sites, and curate information to support automation of the support system.
  • Use internal platforms such as Portal, Foxglove, Kibana, ArgoCD, and Grafana for system analysis; enhance observability and visualization of system behavior.
  • Translate field operations experience into system improvements, enhanced learning, and improved robot skills to optimize performance as deployments scale.
  • Analyze logs, telemetry, SQL/NoSQL data, and container metrics to diagnose failures; reproduce issues in staging; create workarounds or scripted hot fixes; and document issues in Jira or Zendesk.
  • Tune alerting rules, dashboards, and anomaly-detection models, and perform trend analysis against performance targets.
  • Embed at customer sites during go-live, major upgrades, or chronic issue investigations, and identify issues that can be surfaced automatically through observability tools.
  • Write standard operating procedures, runbooks, and self-service articles; contribute to command-line tools and diagnostic scripts in Python or Bash; and mentor TAC on new failure modes.
  • Partner with Product and Engineering on feature hardening, performance tuning, and reliability improvements.
  • Own and execute new product introduction software commissioning at customer sites, including tooling setup, system testing, and calibration.

Desired Qualifications

  • Experience supporting AI/ML inference platforms, including model drift and retraining pipelines.
  • System-level troubleshooting across Linux, networking (TCP/IP, VLANs, VPNs), containers (Docker/Kubernetes), and cloud services (AWS, GCP, or Azure).
  • Familiarity with message queues and real-time data buses (REST API).
  • Exposure to industrial automation or warehouse management systems.
  • Knowledge of CI/CD workflows such as GitHub Actions and ArgoCD, and feature-flag rollouts.
  • Basic understanding of robot kinematics and perception pipelines to communicate with Product Support colleagues.

About the Company

Dexterity

AI-powered robots autonomously load trailers

Dexterity.ai builds AI-powered robotic systems for logistics and supply chain tasks, with a focus on trailer loading. Its robots autonomously pick parcels and place them into crossbelt or tilt-tray sorters at speeds faster than human workers. The system understands its environment in real time without needing external data feeds or warehouse software integrations, which makes deployment easier across different sites. The company sells the robotic hardware and AI software to businesses and also provides consultation services to help integrate and optimize automation. Dexterity.ai aims to improve operational efficiency and employee safety while making logistics work more attractive to workers, helping customers—from small companies to large enterprises like FedEx—achieve faster, safer, and more scalable parcel handling.

Company size
51-200
Company stage
Late Stage VC
Total funding
$291.2M
Headquarters
Redwood City, CA
Founded
2017

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