Agentic Delivery Manager - AI Engineering Manager

We are seeking a highly skilled AI Engineering Manager to lead a team of engineers in delivering production-ready software and AI systems for international clients. This role requires a hands-on leader who is technically proficient, capable of making sound technical decisions, and experienced in managing end-to-end delivery. You will work remotely from Pakistan, full-time, aligned with US working hours, and be expected to join immediately. Success in this role means driving client satisfaction through effective leadership, technical excellence, and clear communication.

Key Responsibilities

- Lead the delivery of software, automation, and AI projects from discovery through production, ensuring alignment with business goals.
- Inspect codebases, architectures, data flows, integrations, and deployment environments to maintain high-quality standards.
- Make credible technical decisions, challenge weak implementations, and investigate failures to guide the team toward root-cause solutions.
- Use AI tools and agentic systems extensively to enhance personal and team productivity, critically validating AI-generated outputs.
- Translate complex requirements into clear, visual delivery plans with defined priorities, ownership, milestones, and success criteria.
- Lead client interactions including kickoffs, technical discussions, delivery reviews, and risk management, maintaining transparent communication.
- Manage a daily delivery rhythm within the engineering pod, identifying and removing workflow bottlenecks to improve team performance.
- Provide constructive feedback, foster accountability, and support engineers’ growth toward future leadership roles.
- Build and maintain client trust through consistent delivery and honest expectation management.

Required Qualifications

- Proven experience leading software or AI engineering teams with a strong hands-on technical background.
- Demonstrated ability to ship software, automation, or AI systems into production environments.
- Expertise in inspecting code and architecture, making informed decisions across engineering, data, infrastructure, and delivery.
- Practical experience using AI tools or agents to boost productivity, with the ability to critically assess AI-generated results.
- Strong understanding of software development workflows, testing, deployment, and production support.
- Skilled at quickly gathering context and converting ambiguity into actionable execution plans.
- Experience coaching engineers and enhancing team performance.
- Excellent stakeholder management and client communication skills, particularly with US or international clients.
- Proficient in professional spoken and written English, capable of creating concise technical documentation and visual plans.
- Strong ownership, judgment, and problem-solving abilities.
- Availability to work full-time during US-aligned working hours.

Preferred Qualifications

- Experience leading engineering pods in consulting, agency, or client-delivery environments.
- Background in delivering LLM applications, AI agents, workflow automations, or AI-enabled products.
- Familiarity with AI coding assistants, agentic development workflows, APIs, integrations, cloud infrastructure, data pipelines, or automation platforms.
- Experience managing multiple technical projects or engineering pods simultaneously.
- Skilled in architecture reviews, code reviews, production incident management, and root-cause analysis.
- Exposure to fast-paced startup or high-growth environments.
- Ability to develop reusable delivery systems, processes, and technical standards.
- Proven track record of mentoring senior engineers and developing future engineering leaders.

The ideal candidate began as a strong individual contributor and evolved into a leader who balances technical depth with people management. You bring clarity, accountability, and ambition to your team without micromanaging. You understand AI as a productivity system, building repeatable workflows while critically validating outputs. You communicate effectively with both technical and non-technical stakeholders and lead with honesty and transparency.

What Success Looks Like

Within your first week, you will understand the client’s business goals, assess the team’s strengths and bottlenecks, inspect technical environments, identify risks, and present a clear delivery plan with defined ownership and milestones. Ongoing success involves maintaining a consistent delivery rhythm, removing blockers, improving technical quality and delivery speed, enhancing AI tool usage, coaching engineers, and building strong client trust that naturally leads to continued collaboration.