D
Dexterity
Forward Deployed Engineer
Skills
Google Cloud PlatformSQL QueriesDockerPythonGrafanaMachine LearningAIAWSGitHubLinuxJiraChange ManagementWarehouse ManagementAzure
2 months ago
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Important information
Contract type:
Permanent
Salary:
$130,000 – $170,000 / year
Location:
Redwood City, CA, USA
Work mode:
Onsite
Published on:
29 August 2026
What they need
- As a Forward Deployed Engineer you are the front line leading Dexterity’s robots into new opportunities
- You will work to bridge any gaps between Dexterity’s standard product and the particular challenges of new customer engagements or new market segments
- Your mission is to bring new applications online in the field and demonstrate all the operational metrics necessary to rapidly unlock fleet-wide scaling at each new customer opportunity
- You will be expected to do system level performance analysis and drive system level solutions through hands on engineering, partnering with other teams across Dexterity, third party partners and the customer
- On-site assignments will involve warehouse conditions (temperature variations, industrial noise) and prolonged standing or walks
- Office desk-based tasks and lab-floor testing
- New Solution Introduction: Ensure successful pilot outcomes by driving new solution operations in the field, resolving early issues, meeting customer KPIs, and preparing the solution to scale rapidly post pilot
- High Quality and Rapid Resolution: Drive fixes and improvements based on field experience with proper methodologies to provide traceability, change management and eliminate repeat occurrences
- Operational Excellence: Release solutions that are ready to scale. Solutions should meet operator expectations for ease of use, up time and operator:robot ratio
- Customer Trust: Become the named technical point-of-contact for one or more strategic sites
- Engineering Feedback Loop: Develop new integrations, robotic skills and capabilities to meet new customer challenges
- Extend and improve methodologies to incorporate field learning into the core platform capabilities towards the goal of general robot intelligence
- Deliver actionable bug reports and reproducible cases that accelerate root-cause analysis
- Field Enablement: Develop new tooling, documentation and provide guidance to application services teams at pilot and production sites. Collect and curate information in a way to drive automation of the support system
- Tooling & Observability:Develop proficiency and leverage internal platforms such as Portal, Foxglove, Kibana, ArgoCD, and Grafana for system analysis
- Enhance observability and visualization to provide better insight to system behavior, particularly as new skills, capabilities and use cases are added
- Drive System Performance Improvement in the Field — The real world always presents subtle new challenges to intelligent systems
- Your primary goal will be to translate field operations experience into better systems, improved learning and enhanced robot skills to optimize top line performance as robot deployments scale
- Diagnose & Resolve Incidents — Analyse logs, telemetry, SQL/NoSQL data, and container metrics to pinpoint failures; reproduce issues in staging; craft work-arounds or scripted hot-fixes; document in ticketing system (Jira/Zendesk)
- Proactive Monitoring — Tune alerting rules, dashboards, and anomaly-detection models; perform trend analysis to track system performance towards KPI targets
- Field Presence — Embed on customer site during go-live, major upgrades, or chronic issue hunts. Understand what flies under the radar and how to surface it automatically through the observability stack
- Knowledge & Automation — Write SOPs, runbooks, and self-service articles; contribute to CLI tools and diagnostic scripts in Python/Bash; mentor TAC on new failure modes
- Continuous Improvement Projects — Partner with Product and Engineering on feature hardening, performance tuning, and reliability improvement
- Own and execute NPI software commissioning at customer sites, including tooling setup, system testing, and calibration- Experience supporting AI/ML inference platforms (model drift, retraining pipelines)
- This role requires broad, systems level understanding of the full robotic tech stack, both software and hardware
- Familiarity with message queues & real-time data buses ( RESTAPI)
- Self-starter mindset with a willingness to take ownership in ambiguous environments
- BS or MS in Computer Science, Robotics or a related discipline, or relevant experience
- Proficient in Python or C++, with experience implementing a large project or product feature
- Bias for Action — sense of urgency in production environments; willingness to “own the ticket” until closure
- Strong analytical and debugging skills; experience parsing logs and telemetry data
- Familiarity with support tools and observability platforms (e.g., Grafana, Kibana, Foxglove, ArgoCD)
- This role is ideal for engineers with a passion for developing robotic solutions that operate in the real world at scale
- Exposure to industrial automation or warehouse management systems
- Data-driven Mindset, ability to instrument, query, and visualize telemetry to inform decisions
- Aptitude for Hands-On Work in Physical-AI Environments — must be willing work across the full breadth of the robot stack from sensors to software
- This position requires frequent travel to customer locations, with typically 50% of time spent on-site
- System-level Troubleshooting across Linux, networking (TCP/IP, VLANs, VPNs), containers (Docker/K8s), and cloud services (AWS/GCP/Azure)
- Clear Communication — translate technical findings into customer-friendly language and crisp bug reports
- Knowledge of CI/CD workflows (GitHub Actions, ArgoCD) and feature-flag rollouts
- Basic understanding of robot kinematics and perception pipelines to converse with Product Support colleagues
- Comfortable working extended hours, on-site or on-call rotations for high-severity incidents
- Bachelor’s degree in an engineering discipline (e.g., Mechanical, Electrical, Industrial, Robotics) or Computer Science — with demonstrable coding skills and a solid grounding in computer-science fundamentals. Equivalent practical experience is welcome
- 2+ years in a SaaS, DevOps, Site Reliability, or Application Support role handling customer-facing production systems
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