Engineering Delivery Manager-Embedded & AI

Engineering Delivery Manager Job Description

Position Summary
We are seeking an experienced and results-driven Engineering Delivery Manager to lead the successful delivery of complex product engineering programs spanning Electrical Engineering, Embedded Systems, Software Engineering, Systems Integration, and emerging AI-driven solutions. The ideal candidate will possess a strong technical foundation, exceptional stakeholder management capabilities, and a proven track record of leading cross-functional engineering teams in a global environment.
The role requires a blend of technical expertise, delivery leadership, product engineering knowledge, and an understanding of AI technologies to drive innovation, operational efficiency, and customer value across engineering programs.
Key Responsibilities
Lead end-to-end delivery of multidisciplinary engineering programs involving Electrical, Embedded, Software, Systems Engineering, and AI-based solutions.
Drive execution of product development initiatives from requirements gathering through design, development, validation, deployment, and lifecycle support.
Collaborate with engineering, product management, architecture, data science, and AI teams to deliver innovative solutions.
Evaluate opportunities to leverage AI technologies, automation, and intelligent workflows within engineering products and delivery processes.
Manage project scope, schedules, budgets, resources, dependencies, risks, and quality metrics.
Establish delivery governance and provide regular executive-level reporting to stakeholders.
Ensure adherence to engineering best practices, quality standards, compliance requirements, and delivery processes.
Mentor teams and foster a culture of innovation, collaboration, continuous improvement, and engineering excellence.
Lead distributed global teams and drive alignment across multiple engineering disciplines.
Required Qualifications
Education
Bachelor’s or Master’s degree in Electrical Engineering, Electronics Engineering, Computer Engineering, Software Engineering, or a related field.
Technical Expertise
Strong background in Electrical and Electronics Engineering.
Solid understanding of Embedded Systems, firmware development, RTOS, hardware-software integration, and system-level debugging.
Strong knowledge of Software Engineering principles, SDLC, and modern application architectures.
Experience managing multidisciplinary engineering programs involving hardware and software products.
Understanding of Systems Engineering, requirements management, traceability, verification, validation, and system integration.
Familiarity with product engineering and product lifecycle management.
AI & Digital Engineering Knowledge
Required
Good understanding of Artificial Intelligence and Generative AI concepts.
Ability to collaborate with AI/ML teams and integrate AI initiatives into engineering programs.
Understanding of AI-enabled product development and intelligent automation use cases.
Awareness of responsible AI, data governance, security, and ethical AI considerations.
Preferred
Experience managing projects involving:
AI/ML-powered applications
Computer Vision solutions
Generative AI platforms
Intelligent automation initiatives
Digital engineering transformation programs
Familiarity with Large Language Models (LLMs) and AI-enabled enterprise solutions.
Exposure to AI frameworks, MLOps practices, and cloud-based AI services.
Understanding of Agentic AI concepts, AI copilots, and workflow automation technologies.
Delivery & Leadership Skills
Proven experience leading large cross-functional engineering teams.
Strong project, program, and delivery management capabilities.
Experience managing global engineering organizations and offshore delivery teams.
Ability to balance customer expectations, technical complexity, quality requirements, and business objectives.
Strong problem-solving, decision-making, negotiation, and conflict-resolution skills.
Experience driving engineering transformations and process improvements.
Communication & Stakeholder Management
Excellent verbal, written, and presentation skills.
Strong customer-facing and executive stakeholder management experience.
Ability to communicate effectively with engineering leaders, architects, product managers, and business stakeholders.
Proven capability to influence decision-making across organizational boundaries.
Preferred Qualifications
Experience in regulated or quality-driven engineering environments.
Experience with industrial automation, intelligent devices, connected products, imaging systems, instrumentation, medical systems, or advanced technology products.
Knowledge of cloud platforms such as Azure, AWS, or Google Cloud.
Familiarity with IoT ecosystems, digital twins, edge computing, and connected engineering platforms.
Experience with Agile, SAFe, Hybrid delivery models, and DevOps practices.
PMP, SAFe, Agile, PRINCE2, or equivalent certification preferred.
Desired Experience
12+ years of overall experience across Electrical, Embedded, and Software Engineering.
5+ years in Engineering Delivery Management, Program Management, or Engineering Leadership roles.
Experience leading complex product engineering programs involving hardware, software, and digital technologies.
Exposure to AI-enabled products, intelligent automation, data-driven engineering, or digital transformation initiatives.