Application Support Engineer

Redwood City · Redwood City · Redwood CityFTmid

EngineeringApplication EngineerApplication Support Engineer

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Overview

At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring,

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EngineeringApplication EngineerApplication Support Engineer

At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work. We’re starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses around the world.

Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven, hardware-agnostic, and have already picked over 15 million goods in production. And did we mention we’re customer-obsessed?

Every decision, large and small, is driven by one question – how can we empower our customers with robots to do more than they thought was possible?Dexterity is one of the fastest growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures.

We’re a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality!

About the Role:

As an Application Support Engineer you are the front line between Dexterity’s NPI and deployed physical AI applications and our customers’ business-critical operations. Your mission is to keep production sites running smoothly, resolve complex software issues before they disrupt performance, and feed insights back to Engineering for continuous improvement.

You’ll dive deep into logs, Data driven results , and configuration states; craft work-arounds or scripted patches; and collaborate closely with the Technical Assistance Center (Tier 1), Product Support (hardware), and Engineering (Tier 3).

This role is ideal for engineers who love debugging live systems, explaining technical details to non-experts, and shipping pragmatic fixes fast—all while laying the groundwork for a future move into Hardware or Software Engineering. This role requires a combination of field readiness, software debugging, data analysis, and direct collaboration with internal engineering and customer-facing teams.

Location: Redwood City, CA. Office desk-based tasks and lab-floor testing.

This position requires extended deployment to customer locations, with up to 80% of time spent stationed on-site. On-site assignments will involve warehouse conditions (temperature variations, industrial noise) and prolonged standing or walks. Assignments may span several weeks or months and are intended to minimize frequent travel by establishing a consistent presence at the customer site.

New Product Introduction: Ensure successful field deployment of new products by driving pilot execution, resolving early issues, and meeting customer KPIs.

High Quality and Rapid Resolution: Own Tier 2 application and software incidents—meet or beat targets for First Response, Containment, and Permanent Fix.

Operational Excellence: Reduce repeat incidents by authoring runbooks, knowledge base articles, and automated diagnostics.

Customer Trust: Become the named technical point-of-contact for one or more strategic sites.

Engineering Feedback Loop: Deliver actionable bug reports and reproducible cases that accelerate root-cause analysis.

Field Team Enablement: Provide real-time support and tooling guidance to application services teams at pilot and production sites.

Tooling & Observability Proficiency:Demonstrate working proficiency and maintaining internal platforms such as Portal, Foxglove, Kibana, ArgoCD, and Grafana. Use observability tools to proactively identify anomalies and reduce customer-reported issues.

Diagnose & Resolve Incidents — Analyze 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 prevent outages.

Field Residency — Embed on customer site during go-live, major upgrades, or chronic issue hunts.

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 Application 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.

Facilitate and approve Merge Requests for P2–P3 bug fixes, ensuring timely and compliant code integration.

System-level Troubleshooting across Linux, networking (TCP/IP, VLANs, VPNs), containers (Docker/K8s), and cloud services (AWS/GCP/Azure).

Programming & Scripting — comfortable reading and writing Python, Bash, and SQL for diagnostics or small tooling.

Data-driven Mindset, ability to instrument, query, and visualize telemetry to inform decisions.

Familiarity with support tools and observability platforms (e.g., Grafana, Kibana, Foxglove, ArgoCD).

Aptitude for Hands-On Work in Physical-AI Environments — must be willing and able to power-cycle, jog, and calibrate super-humanoid robots on the warehouse floor; this role is not “desk-only.”

Strong analytical and debugging skills; experience parsing logs and telemetry data.

Clear Communication — translate technical findings into customer-friendly language and crisp bug reports.

Self-starter mindset with a willingness to take ownership in ambiguous environments.

Bias for Action — sense of urgency in production environments; willingness to “own the ticket” until closure.

Experience supporting AI/ML inference platforms (model drift, retraining pipelines).

Familiarity with message queues & real-time data buses ( RESTAPI).

Exposure to industrial automation or warehouse management systems.

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.

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.

Comfortable working extended hours or on-call rotations for high-severity incidents.