Staff Software Engineer, IQ

Jasper is a marketing agents platform that helps enterprises orchestrate AI agents to execute marketing work at scale. The Staff Software Engineer will drive the technical vision and architecture for the IQ team’s integration pod, designing systems that ingest and model data from external platforms and support reliable AI-powered experiences. The role also involves guiding architectural priorities, addressing customer-specific integration needs, and contributing to engineering and organizational technical direction.

Responsibilities:

• Own the technical vision and architecture for the integration pod, defining how Jasper connects to and ingests data from external systems such as Salesforce and HubSpot
• Architect data ingestion and integration systems that account for the differing constraints of each external system — including API rate limits, authentication, and security concerns
• Design and evolve the context primitives in the IQ layer that depend on external data, and scope the additional engineering work needed to support them
• Partner across the team to address customer-specific integration and design concerns, translating unique requirements into scalable, maintainable solutions
• Proactively understand the business needs of the team, produce a concrete plan of action, and drive it to completion — setting an example for how staff-level work gets done
• Help the team navigate the right set of next projects and architectural goals, and contribute to the org-level technical vision as needed
• Research and propose concrete plans for architectural improvements and upgrades, weighing trade-offs and building alignment across stakeholders

Requirements:

• This is a fully remote role and is open to candidates located anywhere in the continental US
• 8+ years of software engineering experience, with a track record of operating at a staff/principal level of scope and influence
• Demonstrated experience leading major technical initiatives to the finish line — and having stayed long enough afterward to understand and articulate their real-world consequences and trade-offs
• Deep expertise in designing and building integration and data-ingestion systems that connect to multiple external systems with differing constraints (API limits, authentication, security, and compliance)
• Strong distributed systems fundamentals and the ability to architect for reliability, scalability, and maintainability
• AI fluency — a working understanding of core AI concepts (LLMs, agents, copilots, tokens, credits, context windows, RAG, data governance, etc.), applied in the context of building and architecting AI-powered engineering systems
• A proactive, ownership-driven mindset: you identify what the business needs, produce a concrete plan, and execute — while raising the bar for those around you
• Excellent technical judgment and communication skills, with the ability to align teams and stakeholders around architectural direction
• Experience building the data foundations that power LLM-based or AI-driven product experiences
• Familiarity with the systems and tools that marketers rely on (e.g., CRMs and marketing platforms like Salesforce and HubSpot) — though this can also be learned on the job