Staff Forward Deployed Engineer

About the role

Handshake AI builds high-scale data infrastructure for frontier AI labs, supporting the rapid growth of the AI economy. This role centers on leading technical strategy for our most critical customer partnerships while maintaining a hands-on approach to complex engineering deployments. You will own the end-to-end technical lifecycle for strategic customers, translating ambiguous business goals into robust, scalable software solutions. The position requires a rare blend of architectural foresight and deep implementation expertise to ensure successful adoption of our platform. You will operate at the intersection of product, infrastructure, and customer success, driving technical outcomes that define our brand. This role is pivotal in shaping how our engineering organization delivers value to the most demanding AI labs in the industry. You will be expected to mentor others while consistently delivering high-quality, production-ready systems under tight deadlines.

Key facts

What you'll do

• Create the architectural vision and technical strategy for the forward-deployed engineering function.
• Act as the primary technical lead for high-value engagements with AI labs and strategic partners.
• Bridge the gap between customer requirements and core product development by aligning cross-functional teams.
• Build and deploy production-grade systems to solve high-ambiguity technical problems.
• Develop reusable frameworks and design patterns to improve deployment scalability.
• Provide mentorship to senior and mid-level engineers to elevate technical standards.
• Identify and resolve infrastructure or tooling bottlenecks to improve deployment efficiency.
• Define and enforce best practices for cloud infrastructure, security, and reliability across customer deployments.
• Collaborate closely with product managers to prioritize features that deliver maximum impact for enterprise clients.
• Conduct technical discovery sessions to uncover hidden requirements and constraints in customer environments.
• Design integration layers that connect AI lab workflows with our core data infrastructure.
• Own key performance indicators for customer success, including uptime, latency, and deployment frequency.
• Lead post-mortem analyses to extract learnings and drive continuous improvement in our processes.
• Represent the engineering team in executive discussions to align technical capabilities with business goals.

Requirements

• 8+ years of professional software engineering experience, including time in forward-deployed or customer-facing roles at high-growth firms.
• Demonstrated ability to lead technical direction and architecture across multiple systems.
• Expert proficiency in TypeScript and ReactJS, including frontend performance and component architecture.
• Strong knowledge of distributed systems, data modeling, and relational databases like PostgreSQL.
• Experience managing cloud infrastructure on AWS or GCP and maintaining CI/CD pipelines.
• History of leading high-stakes, zero-to-one technical initiatives.
• Strong communication skills for influencing external partners and internal leadership.
• Ability to work in a fast-paced environment where priorities shift based on customer needs.
• Willingness to be on-call for critical production issues affecting marquee customers.
• Commitment to writing clean, maintainable code that can be reviewed and scaled by other engineers.
• Demonstrated success in debugging complex issues in distributed systems under time pressure.
• Understanding of software development lifecycle best practices, including testing and documentation.
• Proven track record of delivering projects on schedule without compromising technical quality.
• Alignment with company values around ownership, transparency, and continuous learning.

Nice to have

• Experience defining technical strategy for AI-native or LLM-powered products in production.
• Background in scaling forward-deployed or professional services engineering teams.
• History of driving platform or infrastructure decisions that increased developer velocity.
• Experience scoping and delivering technical solutions directly with VP or C-level stakeholders.
• Familiarity with MLOps tools and workflows for deploying machine learning models at scale.
• Knowledge of containerization and orchestration platforms like Kubernetes.
• Experience with data pipeline technologies such as Kafka, Spark, or Flink.
• Contributions to open source projects that demonstrate engineering excellence and collaboration.

Practical notes

This role requires 5 days per week in the San Francisco office. The position is full-time and eligible for the stated compensation range plus equity. Travel is not required as part of the core responsibilities. Candidates must be authorized to work in the United States without sponsorship for this role. No specific visa sponsorship is available for this position. Applications will be reviewed on a rolling basis until the role is filled. Deadlines for submission of materials are not applicable, but early application is encouraged to ensure full consideration. The company is committed to building a diverse team and encourages applications from underrepresented groups in technology.