Staff Software Engineer, Solana Staking Protocol
The Role
We are looking for a Staff Software Engineer to serve as Coinbase's Solana Staking Protocol CTO. This is not a typical engineering role. You will combine deep Solana protocol mastery with strategic technical leadership to shape Coinbase's Solana staking trajectory for years to come.
What You'll Do
Define Solana Staking Strategy: Own and drive Coinbase's multi-year technical strategy for Solana staking across validator performance, protocol participation, and product integration. Connect engineering decisions to business outcomes including yield optimization, cost efficiency, and customer growth.
Maximize Validator Performance: Lead the engineering effort to achieve industry-leading APY through validator optimization — including vote accuracy, block production, MEV strategies, commission tuning, and stake distribution. Build systems and tooling that give Coinbase a durable performance edge.
Own Protocol Expertise: Serve as Coinbase's foremost authority on the Solana runtime, consensus mechanism, staking economics, and validator client landscape (Agave, Firedancer, etc.). Evaluate protocol upgrades (e.g., SIMD proposals), assess risks, and proactively position Coinbase for changes before they land.
Drive Cross-Product Integration: Partner with Retail Staking and Institutional Staking product and engineering teams to architect scalable staking integrations across Coinbase's product surface area. Ensure Solana staking is deeply embedded and differentiated in every Coinbase staking product.
Build External Presence & Influence: Represent Coinbase in the Solana ecosystem. Maintain deep relationships with the Solana Foundation, core development teams, other major validators, and ecosystem partners. Speak at major conferences (Breakpoint, etc.) and contribute to protocol governance. Be Coinbase's voice on Solana staking.
Lead Technical Execution: Write production code. Design and build critical infrastructure for validator operations, monitoring, automation, and reliability. Set the technical bar for the team — code reviews, architecture decisions, incident response.
Expand Beyond Staking: Serve as a technical advisor on non-staking Solana initiatives where deep protocol knowledge is required (e.g., Solana tax infrastructure, token programs, new Solana-based products).
Mentor and Scale the Team: Elevate a team of strong engineers (IC4-IC5) through mentorship, architectural guidance, and raising the bar on Solana-specific domain expertise. Define what great Solana engineering looks like at Coinbase.
What We Look For
Deep Solana Protocol Expertise: Extensive, hands-on experience with Solana's architecture — Eg: the runtime, validator mechanics, staking economics, consensus (Tower BFT), turbine, Gulf Stream, and the validator client ecosystem. Understand Solana at the source-code level, not just the API level.
Technical Authority & Execution: Strong IC7-caliber engineer. Design and build complex distributed systems. Write production code in Rust and/or Go. Deep experience with infrastructure at scale — bare metal, cloud, networking, observability.
Strategic Vision: Define year-long technical strategies and connect them to business goals. Break down ambiguous, large-scope problems into executable plans with measurable milestones. Think in terms of competitive advantage, not just engineering correctness.
Ecosystem Presence & Influence: Known figure in the Solana ecosystem. Existing relationships with the Solana Foundation, core contributor teams, and major validators. Track record of public speaking, community engagement, or protocol governance participation.
Cross-Functional Leadership: Partner effectively with product, business, and executive stakeholders. Translate complex protocol dynamics into business-relevant terms for non-technical audiences. Drive alignment across multiple teams and functions.
Passion for Solana: Passionate about the Solana ecosystem, follows protocol developments closely, and has a strong thesis on where Solana staking is headed.
Responsible use of generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuous learning as tools evolve, and applying human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.