Director of Engineering

Client : https://www.cephia.ai/

Physical AI systems — from robotics and autonomous machines to industrial automation —

depend on rich, reliable perception of the real world. Yet today’s sensing architectures rely on

complex stacks of cameras, sensors, and optics that increase cost, power consumption, and

system complexity while still struggling to fill critical perception gaps.

At Cephia AI, we are taking a fundamentally different approach.

Instead of combining multiple sensors and optical modules to separately extract depth, spectral,

and polarization information, we are building a platform that combines nanophotonic

structures with intelligent software reconstruction, enabling compact, low-power multimodal

sensing systems that can dramatically enhance perception systems.

This architecture unlocks new capabilities for Physical AI, allowing machines to perceive their

environment with greater efficiency, robustness, and scalability.

Join us and redefine how machines see the physical world!

Role Overview

We are seeking an experienced and hands-on Director of Engineering to lead the

development of production-grade vision systems and scale our engineering organization. This

role requires a technically credible leader who can guide system architecture across hardware

and software, ensure operational excellence, and build a high-performing team.

You will work closely with founders, customers, and engineers to translate product vision into

deployable computer vision systems, integrating sensing hardware, AI/ML pipelines, and

production software. The ideal candidate combines strong architectural judgment with practical

experience delivering hardware–software systems for real-world deployments.

Location

San Francisco, CA

Key Responsibilities

Build Production-Grade Systems

● Design and deliver reliable, scalable production systems, including computer vision

pipelines and supporting infrastructure.

● Lead development of end-to-end hardware–software systems, from sensing hardware

and embedded processing to cloud and application layers.

● Define system architectures that integrate vision sensors, image signal processors,

perception algorithms, AI/ML pipelines, and production software.

● Ensure high standards for reliability, monitoring, logging, observability, and

performance.

● Anticipate and address scalability and system bottlenecks 12–24 months ahead.

Deliver Vision Systems

● Drive the development of production-ready perception systems, including imaging

pipelines, depth sensing, and multi-modal sensing.

● Ensure tight integration between optics, sensors, firmware, perception algorithms,

and software infrastructure.

● Oversee system validation and deployment for real-world environments and

enterprise use cases.

● Work with hardware partners and internal teams to ensure successful delivery of

integrated hardware–software products.

Lead and Develop the Engineering Team

● Manage and mentor a team of 5–7 engineers, potentially distributed across locations.

● Raise engineering standards, accountability, and execution discipline.

● Provide direct feedback and address performance issues early.

● Foster a high-performance, self-motivated, and collaborative culture.

Interface with Customers

● Participate in enterprise customer discussions when technical clarity is required.

● Explain system capabilities and constraints clearly and manage expectations effectively.

● Step into technical escalations with confidence and credibility.

● Ensure engineering delivery aligns with customer deployments and real-world

requirements.

Partner with Founders

● Translate customer and product commitments into clear engineering roadmaps and

execution plans.

● Provide candid feedback when timelines or scope are not achievable.

● Evaluate engineering decisions in terms of business impact, scalability, and product

readiness.

Qualifications

● 4–6\+ years of experience building and shipping complex software systems or

hardware-software systems.

● Experience with computer vision systems, AI/ML pipelines, distributed systems,

performance-sensitive systems, or hardware-adjacent environments.

● Experience working with imaging systems, sensors, or hardware-adjacent

environments.

● Demonstrated success delivering production systems for enterprise customers.

● Prior experience managing 5–7 engineers directly.

● Strong architectural judgment and production engineering instincts.

● Comfortable operating in fast-moving startup environments.

Ideal Candidate

You are technically credible, execution-oriented, and comfortable owning outcomes. You

combine system-level thinking with practical delivery experience, and you know how to

build teams that ship reliable, integrated systems.

You balance technical depth with pragmatic decision-making, maintain a high bar for

engineering quality, and understand how to deliver real-world vision systems that work at

scale.

Education

● Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Robotics,

Computer Engineering, or a related technical field.

● Strong foundation in computer vision, machine learning, imaging systems, or

embedded systems is highly valued.