Senior Engineering Manager, Co-Intelligent Coaching
New
J
JobgetherAI coaching
Workplace type: Remote; based in the United StatesFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- At least 8 years of software engineering experience, including 4 or more years of direct engineering management experience.
- Required Skills
- AWSPostgreSQLPythonRubyReactCI/CDSoftware Engineering
Requirements
- At least 8 years of software engineering experience, including 4 or more years of direct engineering management experience.
- Demonstrated success developing another leader, such as an engineering manager, technical lead, or engineer taking on leadership responsibility.
- Experience delivering mission-critical software to production and remaining accountable for performance and reliability.
- Experience owning team prioritization, estimation, delivery commitments, and capacity trade-offs.
- People leadership skills, including direct developmental feedback and support through performance challenges.
- Current or recent hands-on experience shipping production code in backend development (Ruby, Python, or similar), web development (React), iOS, or Android.
- Technical breadth to assess architecture across layers and comfort with an expert-generalist engineering model spanning backend, web, and mobile.
- Practical experience directing AI agents through production changes and evaluating the benefits and risks of AI-assisted development.
- Experience building and evaluating AI products, deploying agents to production, monitoring behavior at scale, and measuring prompt or model changes.
- Strong understanding of CI/CD, logging, monitoring, and telemetry.
- Excellent written communication skills for documenting decisions, expectations, and technical standards.
- Familiarity with technologies such as Ruby on Rails, Python (Flask or FastAPI), React, Swift, SwiftUI, Kotlin, PostgreSQL, GraphQL, AWS, Docker, Kubernetes, GitLab, Datadog, and PagerDuty.
Responsibilities
- Lead multiple engineering squads delivering AI-powered coaching experiences from prototyping through production, maintenance, and on-call support.
- Own delivery planning, sprint shaping, prioritization, backlog management, and estimation.
- Balance competing priorities and team capacity, and make delivery decisions.
- Improve engineering cycle time while maintaining software quality, reliability, and operational performance.
- Contribute production code, review architecture, identify design weaknesses, and support incident response.
- Partner with Product Strategists to align product scope, technical feasibility, costs, and timelines.
- Guide AI-driven member experiences, including goal setting, food guidance, daily reflection, and transitions to human coaching.
- Establish standards for AI-assisted engineering, including agent workflows, evaluation practices, and measurable quality expectations.
- Coach engineering managers and emerging technical leaders, and plan team capacity, headcount, skills, and onboarding.
- Strengthen CI/CD, logging, monitoring, telemetry, and incident management, and lead cross-functional engineering improvements.
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