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 GitHub. 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 delivery. Reliability and economics: Own practical service levels and improve availability, latency, throughput, model and infrastructure cost, incident response and operational visibility. Engineering systems: Strengthen code review, automated testing, CI/CD, containerization, infrastructure practices, documentation, release management and production support. Team leadership: Manage, coach and develop engineers; set clear expectations; provide actionable feedback; allocate work thoughtfully; and help recruit the next members of the team. Cross-functional delivery: Partner with Product, Design, Security, Customer Success and go-to-market leaders to turn customer problems into solutions that are valuable, supportable and technically durable. Technology strategy: Evaluate rapidly changing models, frameworks, vendors and open-source tools; make disciplined build-versus-buy decisions and communicate the implications clearly. What Success Looks Like Required Qualifications Bachelor's degree in computer science, software engineering, computer engineering, data science, mathematics, or a closely related technical field. 8+ years of professional software engineering experience, including 2+ years managing engineers or providing formal technical leadership with responsibility for delivery and team development. At least 5 years in a fast paced, start-up environment. Recent hands-on experience designing, building and operating production applications that use large language models or generative AI. Strong backend engineering skills in Python and experience designing production APIs, services, asynchronous workflows and data pipelines. Cross-Cultural Communication: Proven experience collaborating effectively with distributed, international teams where English is spoken as a second language (ESL) Full-stack fluency, including experience with a modern frontend framework such as React, Vue or Angular and the ability to guide end-to-end product decisions. Strong knowledge of distributed systems, cloud infrastructure and data architecture; production experience with AWS is strongly preferred. Experience with CI/CD, automated testing, containers such as Docker, observability and modern software-development practices. Demonstrated ability to evaluate AI system quality, reliability and failure modes beyond traditional deterministic software testing. Experience making consequential architecture and prioritization decisions in an evolving technical environment. Strong people leadership, including coaching, feedback, performance management, work allocation and hiring. Clear written and verbal communication with technical, executive and customer-facing audiences. Preferred Qualifications Master's degree in computer science, artificial intelligence, machine learning, data science, or a related technical discipline. Experience with multi-provider model orchestration, model routing, prompt and context management, tool use, agent frameworks or MCP-based integrations. Experience with retrieval-augmented generation, embeddings, vector databases, knowledge graphs, semantic search or long-term AI memory. Experience creating evaluation datasets, automated model-quality pipelines, guardrails, tracing, red-team tests, A/B tests or human-review workflows. Experience building secure enterprise SaaS products with OAuth or OIDC, SSO, SCIM, role-based access, tenant isolation, secrets management and audit logging. Experience protecting agentic or LLM applications against prompt injection, data leakage, unsafe tool use and untrusted external content. Experience integrating with Microsoft 365, Google Workspace, Salesforce, Atlassian, GitHub or comparable enterprise systems. Experience with infrastructure as code, Kubernetes, event-driven architecture, high-volume APIs or usage-based cost optimization. Experience leading distributed, nearshore or offshore engineering teams in an early-stage or high-growth environment. How You Lead Player-coach: You lead through technical credibility and direct contribution while creating space for others to own and grow. Pragmatic architect: You design for the next stage of scale without turning every decision into a platform project. Quality-minded and fast: You use automation, standards and observability to increase speed and confidence together. Calm under uncertainty: You diagnose clearly, make decisions with incomplete information and communicate risk without drama. Trust builder: You are direct, accountable and generous with context, feedback and credit. Not sure you meet every qualification? Studies show that diverse applicants often hesitate to apply unless they check every box. At Buyers Edge Platform, we value authenticity and inclusion—if you're excited about the role, we encourage you to apply. You might be exactly who we’re looking for! What's in this for you: Great benefits from day one. We offer medical, dental, vision, FSA, company-paid life insurance, and more—plus a 401(k) with company match. Grow with us. Enjoy strong training, development, and competitive pay. Work-life balance. Our flexible PTO policy lets you take time when you need it—no accrual required. #J-18808-Ljbffr Buyers Edge Platform