Senior Engineering Practice Manager, AI-Driven Ops

Cnected; Dallas (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Engineering11 is seeking a Senior Engineering Manager, Engineering Practice to scale how we operate engineering across customer and product domains. You will directly manage engineers across customer and product pods, including offshore partner engineers, contractors, and internal staff, with a focus on staffing, capacity planning, and a repeatable engineering management practice.

You will help define the AI Development Life Cycle (AIDLC) and ensure engineering practices adapt to AI-enabled

Qualifications

• Experience leading multiple software engineering teams and pods.
• Strong background in staffing, capacity planning, and workload management.
• Ability to coach engineers, evaluate performance, and drive accountability across a fast-moving org.
• Experience with offshore/nearshore or external development partners.

Responsibilities

• Directly manage engineers across customer and product pods, including offshore partners.
• Set expectations for performance and provide coaching and feedback.
• Own performance management, career development, onboarding, and ongoing engineer development.
• Help build an engineering culture with high accountability and strong technical standards.
• Oversee pod operations, staffing, and capacity planning across multiple initiatives.
• Own day-to-day relationship with offshore partner, including staffing and performance.
• Develop and improve the Engineering11 engineering management practice, metrics, and visibility.

Skills

Engineering Management

Software Engineering

People Management

Capacity Planning

Team Leadership

Performance Management

Vendor Management

Distributed Teams

Technical Leadership

AI-Assisted Software Development

Job description

Engineering11 is seeking a Senior Engineering Manager, Engineering Practice to scale how we operate engineering across customer and product domains. You will directly manage engineers across customer and product pods, including offshore partner engineers, contractors, and internal staff, with a focus on staffing, capacity planning, and a repeatable engineering management practice.

You will help define the AI Development Life Cycle (AIDLC) and ensure engineering practices adapt to AI-enabled