Applied AI Engineering Delivery Manager

Role Overview

Key Responsibilities

• Manage the end-to-end lifecycle of large-scale application programs, including performance, reliability, scalability, upgrades, enhancements, and system integrations.
• Lead transformation and modernization initiatives incorporating AI-enabled engineering practices.
• Develop project plans, timelines, budgets, estimation models, scenarios, and risk assessments using AI-assisted delivery capabilities.
• Coordinate vendors, system integrators, internal technology teams, business stakeholders, and operations teams to maintain aligned delivery.
• Monitor risks, issues, dependencies, SLAs, service performance, production incidents, and delivery outcomes using AI-assisted analysis and monitoring.
• Lead and mentor application developers, analysts, and support teams while embedding AI and agentic tools into engineering workflows.
• Promote Agile and DevOps practices supported by AI-assisted code review, testing, release management, root-cause analysis, and reporting.
• Establish guardrails and governance for responsible AI use, including human-in-the-loop review, evaluation, and escalation paths.
• Evaluate and pilot emerging AI and agentic engineering tools to improve delivery velocity, quality, and cost efficiency.

Required Skills & Qualifications

• 10 to 12 years of consulting and/or industry experience in technology delivery or engineering management roles.
• Proven experience managing large-scale application programs involving complex business processes and system integrations.
• Hands-on exposure to AI-enabled software delivery using Generative AI or agentic tools for requirements analysis, code generation, testing, or documentation.
• Practical understanding of responsible AI practices, including guardrails for hallucination, bias, and drift, and evaluation harnesses before and after deployment.
• Experience leading mid-to-large engagements or workstreams and mentoring multiple team members across cross-functional delivery teams.
• Strong technical delivery background spanning system delivery, application modernization, data integration, or technology operations.
• Bachelor's degree in Computer Science, Engineering, Business, or a related field.
• Experience with modern agentic AI engineering tools such as Claude Code, Claude Co-work, OpenAI Codex, Cursor, or Visual Studio Code.
• Experience applying Agile and DevOps practices to AI-assisted engineering workflows.
• Experience with AI-driven monitoring, anomaly detection, automated reporting, and delivery analytics.
• Willingness to travel 0-20% based on client and engagement requirements.

Applicants will be asked to answer the following qualifying questions when applying for this position:

• 1Do you have 10+ years of experience in technology delivery or engineering management roles?
• 2Do you have hands-on experience using Generative AI or agentic tools for software delivery, including requirements analysis, code generation, testing, or documentation?
• 3Do you have experience implementing responsible AI practices, including guardrails for hallucination, bias, and drift, along with evaluation harnesses before and after deployment?