Infinity Constellation
Engineering Manager (AI) - Supernal
2mo ago
LeadRemoteaiautomationperformance managementarchitectureteam leadershiphiringcoaching
Lead multiple engineering teams building and shipping production-grade AI systems with focus on quality, delivery, and team development.
Responsibilities
- As a Mason Manager (Engineering Manager), you will lead multiple pods of Junior + Senior Masons responsible for building and shipping production automation and agentic systems for customers.
- This is a highly technical people leadership role. You will be accountable for what your pods ship: architecture decisions, quality bars, reliability, documentation, and delivery outcomes. You’ll also invest heavily in hiring, coaching, and performance management — building a team that can deliver at scale with consistent craft.
- You are not a “process-only” manager. You will stay close to the work: reviewing designs, unblocking complex integrations, setting engineering standards, and acting as the escalation point for production issues and delivery risk.
- Lead multiple Mason pods and own delivery outcomes: scope, milestones, quality, and on-time execution
- Translate ambiguous customer/internal requests into clear plans, acceptance criteria, and execution strategy
- Set and enforce production-quality standards for Mason builds (testing, monitoring, runbooks, documentation, rollout plans)
- Serve as technical escalation for difficult problems: auth/permissions, integrations, data modeling, reliability, and failure recovery
- Establish and evolve team processes: scoping discipline, QA gates, review checklists, incident/postmortem loops, and continuous improvement
- Drive prioritization and capacity planning across pods; identify the critical path and remove blockers fast
- Partner with Delivery Leads and stakeholders to manage tradeoffs, timelines, and expectations (including client-facing escalations when needed)
- Hire and build the team: define roles, run interview loops, calibrate, close candidates, and improve onboarding
- Manage performance: set expectations, deliver feedback, coach growth, and handle underperformance clearly and fairly
- Develop leaders within the Mason org: mentoring, delegation, and building strong ownership at every level
Other
- At Supernal, we help SMBs hire their first AI employee. Our AI teammates are built with intelligent, agentic workflows and deployed on our proprietary platform. We don't build tools — we deliver working, value-generating AI Employees.
- Our AI Platform Engineers, known internally as Masons, are the builders behind these systems. As we scale delivery, we need a Mason Manager to lead multiple pods of Masons and ensure we ship reliable, production-grade AI Employees — predictably and at high quality.
- Have 5+ years of experience building production systems as a software/automation engineer, plus 2+ years of engineering management or tech-leadership experience (people management strongly preferred)
- Have managed multiple concurrent workstreams (pods/squads) with shared standards and predictable delivery
- Are deeply comfortable with integrations: APIs, webhooks, auth (OAuth/API keys), and data stores (Postgres/Supabase)
- Can reason about reliability in automation/agentic systems: idempotency, retries/backoff, rate limits, auditing, and safe failure modes
- Have a strong quality mindset: unit/integration/E2E testing, regression prevention, monitoring/observability, and runbook culture
- Have experience with applied AI delivery patterns: prompt iteration, eval harnesses, human-in-the-loop QA, and LLM observability
- Enjoy people management and have real examples of coaching, feedback, and performance management
- Have run hiring loops end-to-end: defining roles, interviewing, calibration, and closing candidates
- Communicate clearly and fluently in English — written and verbal — and can align technical and non-technical stakeholders
- Thrive in fast-paced, ambiguous environments and take ownership without being asked
- Multiple Mason pods ship production AI Employees predictably, with clear milestones and minimal thrash
- Builds are reliable in the wild: fewer incidents, fast recovery, strong observability, and durable runbooks/SOPs
- Engineering standards are consistently applied across pods (testing, documentation, QA gates, and design clarity)
- Stakeholders have high trust: timelines and tradeoffs are communicated early and crisply
- The Mason org scales through strong hiring and onboarding; new Masons ramp quickly and ship meaningful work
- Team performance improves over time through coaching, clear expectations, and a high-accountability culture