VP Software Engineering

Planted•Oakland, CA

9d•Onsite

About The Position

Energy is the binding constraint on human progress. Solar and storage are the lowest cost sources of new energy generation, but the conventional project delivery model has not changed in 30 years and deployment cannot keep pace with demand. Planted is turning power plants from projects into products. Our software turns raw land into a build-ready power plant in minutes instead of months. Our hardware delivers twice the energy on every acre. Our robots put steel in the ground so output scales with production lines instead of headcount. We're looking for a technical leader to build and scale the software organization at the center of that transition – from the autonomy stack running on our robots to the AI systems that will make deployment even faster. You will own the architecture, roadmap, and team driving Planted's next phase of growth. We don't wait for abundance. We build it. About The Role Software is both the brains of our machines and the connective tissue of Planted operations. You will lead and grow a software organization spanning three domains: autonomous robotic vehicle software, our suite of web-based power plant design, build, and operate tools, and an emerging portfolio of AI agents that automate engineering, estimation, and operations workflows. We are looking for a pragmatic technical leader with a track record of building high-performing, multi-disciplinary software teams. You must be deep enough technically to drive key architectural decisions across the vertically integrated platform, and strategic enough to drive and execute on the product roadmap. You have systems literacy (e.g., how data moves from a robot's camera into an ML pipeline) and prioritize delivery mechanics over heavy-handed project management. Our robots are building projects in the field today and our design software is in front of customers. Your mandate is to scale the product and the team to support our current 10x year over year growth in megawatts deployed. The Team: You will join a group at the intersection of deep tech and massive physical infrastructure. Our engineering core brings robotics and automation DNA from SpaceX and Tesla, working directly alongside veteran energy developers. We are led by repeat founders with a successful prior exit (Cogenra to SunPower). Planted is backed by leading investors in energy and Physical AI, including Breakthrough Energy Ventures, Khosla Ventures, Piva Capital, and RA Capital.

Requirements

10 to 15+ years of software engineering experience, including 5+ years leading engineering teams (senior ICs and managers) shipping production systems.
Deep expertise in full stack software development involving hardware and software integration like robotics, IoT, or industrial automation.
Track record shipping robotics, autonomous vehicles, or hardtech software into the field at scale—with a strong focus on fleet reliability, continuous testing, and real-time observability.
Broad leadership capability across platform/full-stack teams, cloud infrastructure, data systems, or applied AI/ML groups outside your core specialty.
Systems architecture judgment with strong understanding of how technologies work together (e.g., middleware, pub/sub architectures, web services, and ML pipelines).
You do not need to write the C++ on the robot, but you must understand edge compute, latency, and hardware-in-the-loop testing.

Nice To Haves

Experience in construction, agriculture, mining, defense, logistics, or autonomous vehicles operating off-pavement (e.g., Waymo, Cruise, Bedrock Automation).
Strong understanding of modern software deployment and containerization (Docker).
Experience with CI/CD, release pipelines, and edge deployment strategies, focusing on how code reliably gets to the machine.
Experience building, rebuilding, and managing AI-integrated software development platforms and teams.
Familiarity with the complexities of deploying field-robotics software (e.g., ROS2, vehicle navigation, and autonomy stacks).
You understand the unique delivery challenges of robotics compared to traditional software.
Experience with LiDAR, stereoscopic/IR cameras, object detection, spatial mapping, and SLAM in dynamic outdoor environments.
Strong understanding of middleware, pub/sub architectures alongside web services, backend technologies, and ML pipelines.
Deep understanding of software platforms working with geospatial data (GIS, CAD engines, 3D modeling, or automated parametric design).
Exposure to automated manufacturing execution systems (MES) managing statistical process control, telemetry monitoring, or fleet analytics in hardtech, renewable energy environments, or advanced manufacturing.

Responsibilities

Build, scale, and mentor a high-performing, multi-level software organization, including direct management of engineering managers, principal engineers, and system architects.
Foster a culture of technical excellence, accountability, and continuous growth.
Recruit and retain top-tier software talent across cloud, spatial/CAD, embedded, and robotics domains while allowing technical experts to own the architecture.
Own the software roadmap and drive the predictable, on-time delivery of complex, multi-system software projects across multiple products.
Set clear expectations, communicate progress, and align software deliverables.
Collaborate seamlessly with the Commercial team, Hardware Engineering, and Project Operations.
Make the build-vs-buy, stack, and platform decisions that will hold up at 100x scale.
Lead development across our core platforms: Power Planter (automated layout, engineering, and costing), Build View (autonomous fleet management, field deployment, and QA/QC), and Operate View (inspection, operations, and maintenance tools for large-scale solar plants).
Lead the engineering teams deploying the full software stack across our autonomous field machine fleet (fleet logic, behavior trees, and path planning, modern and classical controls, ROS2, etc.).
Own the telemetry and data infrastructure that monitors production with statistical process control and turns every installation into training data for better models and improved machine productivity.
Build the team and roadmap for AI agents that automate design, estimation, project delivery, and operations workflows, grounded in the data our robots and projects generate.