As a Senior Systems Engineer, you'll design and scale system architectures for robotics, integrating hardware and cloud services, while mentoring engineers and driving technical decisions.
About the Role
FieldAI is building the intelligence layer that enables autonomous robots to operate reliably in complex, unstructured, real-world environments. As a Staff Systems Engineer, you will play a critical role in architecting and scaling end-to-end systems that span robot hardware, sensing, embedded software, edge computing, and cloud infrastructure.
This is a senior, hands-on technical leadership role with broad ownership. You will work closely with robotics, autonomy, platform, and infrastructure teams to design systems that are robust, observable, and deployable at scale in the field.
Learn more at https://fieldai.com
Why This Role Is Open
As FieldAI expands globally and establishes its Singapore engineering hub, we are scaling our robotics platform to support:
Increased deployment of autonomous systems in real-world industrial environments
More complex sensor stacks and edge intelligence
Higher reliability, observability, and system-level rigor across hardware, firmware, and cloud
We are opening this role to bring senior systems leadership on the ground in Singapore—someone who can own cross-layer architecture, mentor engineers, and help shape the technical foundation of our next phase of growth.
What You’ll Get To Do
- Own system-level architecture across robotics hardware, embedded software, edge compute, and cloud services
- Design and evolve distributed, event-driven systems for real-time data ingestion, monitoring, and control
- Partner with autonomy, perception, and platform teams to integrate sensing, algorithms, and infrastructure
- Drive technical decisions around reliability, scalability, observability, and deployment
- Lead complex technical initiatives and mentor engineers across multiple teams
- Act as a bridge between product needs and deep engineering execution
What You Have
- 8+ years of experience in systems engineering, robotics, embedded systems, or distributed platforms
- Strong background in end-to-end system architecture spanning hardware, firmware, edge, and cloud
- Hands-on experience with embedded systems, sensors, or IoT devices operating in real-world conditions
- Proven experience designing or operating distributed or microservice-based systems
- Strong understanding of event-driven architectures, messaging queues, and real-time systems
- Experience deploying and operating systems on cloud infrastructure (e.g., Kubernetes, CI/CD pipelines)
- Ability to lead technically across teams and influence architecture at an org-wide level
- Comfortable working in ambiguous, fast-moving environments
The Extras That Set You Apart
- Experience with robotics platforms, autonomous systems, or industrial automation
- Background in physiological sensing, computer vision, or sensor fusion
- Experience with edge AI / on-device inference
- Familiarity with observability, monitoring, and reliability engineering in production systems
- Prior experience as a tech lead, staff engineer, or principal engineer
- Experience building or scaling systems across multiple geographies or deployments
- Exposure to safety-critical or mission-critical systems
Why FieldAI?
- Work on real-world autonomy, not simulations or demos
- Influence architecture decisions that directly impact deployed robots
- Collaborate with a globally distributed, deeply technical team
- Help build and shape FieldAI’s Singapore engineering presence from the ground up.
Top Skills
Ci/Cd Pipelines
Cloud Infrastructure
Edge Computing
Embedded Software
Event-Driven Systems
Kubernetes
Robotics Hardware
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What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
