VP / SVP of Engineering
Cedar Park, TX
Full-time
Remote
2 months ago
About the role
Description
VP / SVP of Engineering
FLSA Status: Exempt
Department: Operations & Technology
Reports To: COO
Role Overview
Terradepth has built the category-defining ocean intelligence platform. The VP/SVP of Engineering will lead the company's engineering efforts from operational to scaled market leadership—owning the systems, team, and velocity required to meet growth needs.
This is a builder’s role. You will take a complex, integrated product (hardware + software + data) and evolve it into a scalable, repeatable, capital-efficient platform. The team has delivered an incredible amount of momentum coming into 2026 and we are expanding our leadership to align our sales efforts with our product delivery. You must operate with urgency in ambiguous conditions, make high-quality tradeoffs, and build both the technology and the team required to win the market.
About The Role
You Are Accountable For
Requirements
What Success Looks Like (12 Months)
Minimum Qualifications
Ideal Experience / Leadership Profile
What’s Different About This Role
VP / SVP of Engineering
FLSA Status: Exempt
Department: Operations & Technology
Reports To: COO
Role Overview
Terradepth has built the category-defining ocean intelligence platform. The VP/SVP of Engineering will lead the company's engineering efforts from operational to scaled market leadership—owning the systems, team, and velocity required to meet growth needs.
This is a builder’s role. You will take a complex, integrated product (hardware + software + data) and evolve it into a scalable, repeatable, capital-efficient platform. The team has delivered an incredible amount of momentum coming into 2026 and we are expanding our leadership to align our sales efforts with our product delivery. You must operate with urgency in ambiguous conditions, make high-quality tradeoffs, and build both the technology and the team required to win the market.
About The Role
- Platform & System Ownership (Hardware + Software + Data)
- Own the end-to-end Terradepth system:
- Cloud infrastructure and Absolute Ocean (AO) platform
- Data ingestion, transmission, and processing pipelines
- Oversee:
- Autonomous survey hardware (robotics, sensors, onboard compute)
- Drive the transition from custom deployments to a standardized platform
- Ensure tight integration across hardware, data, platform and customer delivery
- Optimize for reliability, scalability, and speed to deployment
- Scale systems from TB to PB environments while maintaining performance
- Deliver seamless software deployments across public and private clouds in addition to on-premise hardware to meet varied customer security and deployment use cases.
- Experience with AWS (including GovCloud), Python, Go, React (TypeScript and JavaScript), PostgreSQL, and Swagger/OpenAPI development and integration
- Execution, Velocity & Operational Performance
- Build a high-velocity engineering organization that delivers against aggressive growth goals
- Own delivery of engineering commitments tied directly to velocity and revenue
- Establish and maintain clear prioritization, planning, and accountability systems
- Make fast, pragmatic tradeoffs; avoiding the over-engineering trap
- Partner closely with field operations to:
- Improve mission success rates and uptime
- Reduce deployment friction and failure points
- Accelerate feedback loops from field to engineering and product
- Drive predictable execution across hardware, firmware, and software
- Team Building & Leadership at Scale
- Build and scale a world-class, multi-disciplinary engineering team:
- Software, data, hardware/robotics, systems engineering, and cloud operations
- Hire and develop leaders who can scale with the company
- Create clear ownership with strong system-level accountability
- Foster a culture of:
- Ownership and urgency
- High standards and accountability
- Resourcefulness under constraint
- Continuous growth and improvement
- Balance senior leadership tenets with a team of independent, high-output builders
- Architecture, Data & AI
- Own system architecture across:
- Data ingestion (internal + third-party normalization and ingestion)
- Processing pipelines (geospatial, bathymetric)
- Storage, compute, and distribution
- Customer-facing AO applications
- Lead the integration of AI/ML and agentic systems across the platform:
- Automate data processing, QA, and anomaly detection
- Enable intelligent mission planning and adaptive survey operations
- Power customer-facing insights, recommendations, and workflows
- Deploy internal agentic systems to improve engineering productivity, support and operations efforts
- Drive adoption of agentic AI in:
- Customer support and service workflows
- Data interpretation and delivery
- Internal tooling and decision support
- Create and maintain an AI plan that provides speed, execution and reduction of manual work while keeping human-in-the-loop at all times
- Balance long-term architectural integrity with near-term delivery speed
- Capital Efficiency & Unit Economics
- Own system-level cost structure:
- Cloud and data processing
- Hardware build, deployment, and lifecycle
- Drive continuous improvement in:
- Cost per km² surveyed
- Cost per TB processed
- Make disciplined build vs. buy decisions
- Ensure engineering investments translate into scalable margins
- Establish visibility into capacity planning and resource utilization
- Product, Customer & Commercial Alignment
- Partner closely with Product, Operations, Business Development
- Ensure engineering outputs enable repeatable, scalable offerings
- Support technical solutioning for key deals when needed
- Eliminate one-off builds that do not strengthen the core platform
- Ensure fast, reliable delivery from survey to data to direct customer value
- Metrics That Matter
You Are Accountable For
- Engineering velocity and on-time delivery
- Mission success rate and uptime
- Platform reliability and performance (>99.5%)
- Data processing speed and quality
- Cost per km² surveyed
- Cost per TB processed
- Hardware reliability (MTBF, failure rates)
- Impact of AI/automation on efficiency and customer outcomes
- Security and Compliance
- Experience establishing security policies and practices to meet all required cybersecurity compliance goals including CMMC L2 and NIST 800-53. Leading to future FedRamp efforts
Requirements
What Success Looks Like (12 Months)
- System is evolving into a repeatable, scalable platform
- Engineering velocity increases without sacrificing quality
- Teams are operating with defined engineering processes and workflows
- Mission success rates and uptime materially improve
- Unit economics show clear improvement and path to margin expansion
- Agentic AI is embedded across platform, operations and customer experience
- Platform reliability exceeds 99.5%
- Strong, scalable engineering leadership team is in place
- Engineering is a core competitive advantage in winning and delivering business
Minimum Qualifications
- 10-15 years of engineering experience across software and hardware systems
- Proven experience in venture-backed or high-growth environments
- Track record scaling products and teams from early-stage to high growth-stage
- Experience delivering complex, integrated software and hardware systems (robotics, autonomy, or sensor-driven platforms)
- Experience with AI/ML systems and practical application of automation at scale
- Background in real-world operating environments (offshore, energy, defense, aerospace, etc.)
- Strong technical depth in:
- Distributed systems and cloud infrastructure
- Embedded systems and/or robotics
- Large-scale data pipelines (TB–PB)
- Experience with AWS (including GovCloud), Python, Go, React (TypeScript and JavaScript), PostgreSQL, and Swagger/OpenAPI development and integration
- Demonstrated ability to deliver quickly under constraints
- Proven success translating bespoke engineering projects/deployments into standardized, commercially viable products and repeatable processes
Ideal Experience / Leadership Profile
- Development of autonomous systems, marine robotics, or offshore platforms
- GIS tools and managing Geospatial data (e.g. ESRI, EIVA, QINSy, CARIS)
- Experience deploying AI/agentic systems in production environments
- Defense, maritime, or energy sectors
- Scaling integrated hardware + software platforms in venture-backed companies
- Builder: Has scaled companies from 50 to 250 to 500
- High-Velocity Operator: Moves fast, ships often, and learns quickly
- Risk-Tolerant: Makes decisions with incomplete information
- Capital Efficient: Optimizes for impact per dollar spent
- Hands-On: Will dive deep when needed
- Talent Magnet: Attracts and develops high-caliber builders
- Relentless: Drives outcomes in complex, real-world environments
What’s Different About This Role
- You are building a category-defining platform
- You will integrate hardware, software, data, and AI into one system
- You will embed agentic AI across the company, not just as a feature
- You will balance speed, scale, and cost every day
- Your impact will directly shape the company’s trajectory and market leadership
Skills
Construction