Manager, Engineering

CollectivIQ is building an AI workforce platform for the enterprise. Our products give employees a team of AI specialists that can work across email, files and business systems; compare answers across more than 30 models from 10+ providers; build and host business applications from plain-language requests; and turn organizational knowledge into a governed, source-backed company memory.

The platform is designed for real work, not isolated experimentation. CollectivIQ combines Digital Direct Reports, multi-model Chat, Apps and Gigabrain with enterprise-grade identity, permissions, approvals, auditability and data controls. We are creating a new category of software that helps organizations move faster while maintaining trust, security and human oversight.

The Opportunity

CollectivIQ is hiring a Manager, Engineering to serve as a foundational technical leader for the next stage of the platform. This is a hands-on player-coach role with responsibility for production architecture, software delivery, engineering quality and the growth of a small, high-performing team.

You will work closely with the VP of Data Science & AI and the Senior Product Manager to build systems that connect large language models, enterprise knowledge, business applications and action-taking AI specialists. The work spans multi-model orchestration, agent execution, retrieval and memory, enterprise integrations, permissions, auditability, observability and cloud-scale product engineering.

The right person is equally comfortable reviewing an architecture, debugging a production issue, writing high-leverage code, coaching an engineer and explaining a technical tradeoff to a business leader. You will help decide not only what we build, but the standards and operating practices that allow CollectivIQ to build quickly without compromising security, reliability or customer trust. In this role, you will work closely on a daily basis with our distributed engineering and operations teams, primarily based in Peru.

You will be a bridge between our domestic and international teams to ensure smooth alignment and execution.

We are unable to offer work sponsorship for this role.

What You Will Own

• Technical architecture:
  Set and evolve the architecture for a secure, scalable AI SaaS platform spanning Digital Direct Reports, multi-model Chat, AI-built Apps, Gigabrain and external system connections.
• Hands-on engineering:
  Contribute meaningful production code and technical designs while leading delivery; remain close enough to the codebase to make informed decisions and raise engineering quality.
• AI orchestration:
  Design and improve model selection, routing, parallel execution, synthesis, context management, tool use and fallbacks across multiple model providers.
• Agents and safe action:
  Build reliable patterns for AI specialists to plan and execute work in customer systems using scoped permissions, approval gates, idempotency, audit trails and clear failure recovery.
• Knowledge and retrieval:
  Advance source-backed retrieval, memory, embeddings, vector search, knowledge relationships, freshness and role-based confidentiality for enterprise information.
• AI quality and evaluation:
  Establish offline and online evaluations, test datasets, quality thresholds, regression testing, observability and feedback loops for probabilistic AI behavior.
• Enterprise platform engineering:
  Lead the design of APIs, services, data flows, asynchronous workloads and integrations with systems such as Microsoft 365, Google Workspace, Salesforce, Atlassian and Git Hub.
• Security and governance:
  Embed least-privilege access, tenant isolation, secrets management, secure handling of untrusted content, prompt-injection defenses, logging and privacy controls into system design and…