Senior Engineering Manager, Applied AI
Leads a lean Applied AI engineering team within Genius AI at HearstLab, building and deploying AI-driven solutions across the business — running one-week sprints, demos, AI model selection, and evaluation practices to drive measurable go-to-market outcomes. Requires 7+ years of engineering, 2+ managing, and hands-on agentic AI experience; hybrid in NYC or SF.
- Compensation
- Not disclosed
- Location
- New York City, New York, United States
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Full time
- Experience
- 2+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- Personally built and shipped agentic systems with real users in the last 12 months, able to discuss architecture, challenges, costs, and outcomes
- Can articulate how to measure AI effectiveness beyond adoption metrics, with clear opinions on the right metrics and their limitations
- Prefer to grow output rather than headcount, raising team expectations through AI-driven workflow changes
- 7+ years of software engineering experience, including 2+ years managing engineers while remaining hands-on in the code
- Scrappy generalist with cross-functional instincts; has worked closely with sales, marketing, or operations teams to drive adoption
- Ties engineering work to business outcomes (pipeline, revenue, time saved, cost avoided) and reports on them clearly
- Comfortable building lightweight processes and adapting quickly to change
- Regular in-office attendance 3–4 days per week at NYC or San Francisco office, with required presence Tuesdays and Thursdays
Full description
Genius AI is seeking an Engineering Manager, Applied AI to join our team and help transform how we work by building and deploying AI-driven solutions across the business. You will lead a lean team of engineers, drive measurable go-to-market outcomes, and set the standard for what an AI-native engineering team looks like.
Responsibilities will include:
- Build and lead a team of engineers, setting the bar for AI-native engineering practices
- Drive measurable go-to-market outcomes by partnering across Engineering, Sales, Marketing, Finance, Legal, and People to prioritize a company-aligned backlog anchored to pre-agreed metrics and executive-trusted readouts
- Run a tight engagement loop with intake, one-week sprints, Friday demos, and clean handoffs to ensure partner teams own what was built and Applied AI can focus on the next challenge
- Establish evaluation practices to ensure every AI product team has a measurable quality bar for safe, rapid development
- Select and route to the right AI models, using frontier models for new use cases and more efficient models as use cases mature
- Collaborate with DevEx to experiment with and implement new ways of working, turning successful experiments into shared standards and documentation
You’re a great fit if you:
- Have personally built and shipped agentic systems with real users in the last 12 months and can discuss the architecture, challenges, costs, and outcomes
- Can articulate how to measure AI effectiveness beyond adoption metrics, with a clear opinion on the right metrics and their limitations
- Prefer to grow output rather than headcount, and have raised your team’s expectations through AI-driven changes in workflow
- Have 7+ years of software engineering experience, including 2+ years managing engineers while remaining hands-on in the code
- Are a scrappy generalist with cross-functional instincts, having worked closely with sales, marketing, or operations teams to drive adoption of new solutions
- Tie engineering work to business outcomes such as pipeline, revenue, time saved, or cost avoided, and report on them clearly
- Are comfortable building lightweight processes as needed and adapting quickly to change
Additional Information:
- This role requires regular in-office attendance (3–4 days per week) at our NYC or San Francisco office, with required presence on Tuesdays and Thursdays
- Genius AI is an Equal Opportunity and Affirmative Action Employer, committed to creating a supportive and empowering workplace for all employees