Azalio
AI Delievery Lead
Gurgaon·Full Time·On-site·4-6 years
AI project managementmachine learning lifecyclestakeholder communicationdata strategymodel deploymentcross-functional leadershiprisk managementAI ethicscloud platformsperformance optimizationteam collaborationagile methodologiesproblem-solvingtechnical documentationvendor management
Role Overview
AI Delivery Lead
Location: Gurgaon, India
Employment Type: Full Time
Experience Level: 4-8 years
- We are seeking a highly skilled and motivated AI Delivery Lead to oversee and drive the successful execution of AI projects from inception through deployment.
- This role requires a strategic thinker with strong expertise in managing the machine learning lifecycle, ensuring alignment with business objectives, and fostering collaboration across diverse teams.
- The AI Delivery Lead will play a critical role in shaping data strategy, managing risks, and upholding AI ethics while optimizing performance on cloud platforms.
Required Qualifications and Experience
Soft Skills
- Excellent stakeholder communication and interpersonal skills.
- Strong leadership and team collaboration capabilities.
- Effective problem-solving and decision-making skills.
- Ability to manage multiple priorities in a fast-paced environment.
- Detail-oriented with strong organizational skills.
- Adaptability and openness to continuous learning and improvement.
What You Will Do
- Lead end-to-end AI project management, ensuring timely delivery and alignment with organizational goals.
- Develop, document, and maintain detailed Methods of Procedure (MOPs) for AI model deployment and lifecycle management.
- Collaborate with cross-functional teams including data scientists, engineers, product managers, and stakeholders to drive project success.
- Oversee integration and testing processes to validate AI models and solutions before production deployment.
- Manage risk by identifying potential challenges and implementing mitigation strategies throughout the project lifecycle.
- Champion AI ethics and compliance, ensuring responsible AI practices are embedded in all project phases.
- Optimize AI model performance leveraging cloud platforms and scalable infrastructure.
- Facilitate effective communication between technical teams and business stakeholders to ensure transparency and alignment.
- Lead vendor management activities related to AI tools, platforms, and services.
- Promote agile methodologies and continuous improvement within the AI delivery team.
- Prepare and maintain comprehensive technical documentation to support knowledge sharing and operational continuity.
Skills and Experience
- Proven experience in AI project management and the complete machine learning lifecycle.
- Strong knowledge of data strategy formulation and implementation.
- Expertise in AI model deployment, monitoring, and performance optimization on cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with AI ethics frameworks and compliance standards.
- Hands-on experience with agile methodologies and tools.
- Technical proficiency in managing integration and testing of AI systems.
- Experience with vendor management related to AI technologies and services.
Preferred Experience
- Certifications in AI, machine learning, or project management (e.g., PMP, Agile, Certified AI Practitioner).
- Specialized training in AI ethics and governance.
- Experience with advanced AI platforms and tools beyond core cloud services.
- Knowledge of emerging AI trends and technologies.
How We Work
Ownership-led delivery
We expect every team member to understand the problem, take responsibility and follow through.
Architecture-grounded engineering
Design is validated before implementation begins. Standards and governance are embedded throughout.
Evidence over assumption
Delivery is supported by documentation, runbooks, test results and acceptance evidence.
Continuous improvement
Lessons from every engagement are captured and reused across practices and programs.
Application Process
- 1Submit your application with CV and cover note below
- 2Our team will review your background and reach out within a reasonable timeframe
- 3Initial conversation to understand your experience and explore mutual fit
- 4Technical and role discussion with the practice team
- 5Offer and onboarding