Experience
20 - 30 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Director Engineering
Job Type
Not specified
Job Description
The Director of Technology AI Solutions will be responsible for developing and executing the technology roadmap , leading cross-functional AI engineering teams, and ensuring the scalability, security, and operational success of iTCart s AI solutions. The role involves architecting enterprise AI infrastructure , integrating cutting-edge machine learning models , and aligning technology with business strategy and market demands . You will collaborate closely with global technology leaders to build scalable, secure, and next-generation AI platforms.
This role is ideal for a hands-on AI technology leader who thrives on building high-performance AI engineering teams, driving complex AI/ML product development, and scaling Enterprise SaaS Solutions globally.
Key Objectives:
- Define and implement state-of-the-art AI technology strategies for BFSI, healthcare, real estate, manufacturing, supply chain, education, retail, and cybersecurity.
- Oversee the design, development, and deployment of AI-powered SaaS platforms.
- Lead AI and cloud architecture, ensuring performance, reliability, and cost optimization.
- Drive enterprise AI adoption, delivering impactful AI solutions for global enterprises.
Key Responsibilities:
Technology Strategy AI Innovation
- Define and drive the technology vision, roadmap, and AI-driven innovation strategy.
- Develop AI-powered, cloud-native architectures, ensuring security, scalability, and efficiency.
- Spearhead cutting-edge AI/ML model development and integration across platforms.
- Research and implement emerging AI trends, frameworks, and open-source technologies.
Product Development Engineering Excellence
- Lead the design, architecture, and deployment of AI-driven SaaS solutions.
- Oversee full AI/ML lifecycle management, from data ingestion to model deployment and continuous learning.
- Implement cloud-based AI infrastructure on Azure, AWS, and hybrid-cloud environments.
- Optimize AI pipelines for real-time data processing, NLP, predictive analytics, and automation.
Enterprise AI Strategy Market Impact
- Align AI technology initiatives with business objectives and market demands.
- Architect scalable AI-powered enterprise infrastructure for multiple industries.
- Ensure AI solutions comply with industry-specific regulations (GDPR, HIPAA, BFSI security frameworks).
- Establish AI governance, ensuring responsible AI use and bias mitigation.
Team Leadership Collaboration
- Lead and mentor global AI engineering teams, fostering collaboration and innovation.
- Work cross-functionally with CTO, Product Management, and Business Development teams.
- Build a culture of technical excellence, research-driven innovation, and continuous learning.
Mandatory Qualifications :
- 20+ years of experience in technology leadership roles, focusing on AI-powered software engineering, SaaS solutions, and cloud computing.
- Expertise in designing and scaling AI-driven platforms across BFSI, healthcare, real estate, manufacturing, supply chain, education, retail, and cybersecurity.
- Deep technical proficiency in AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), cloud platforms (Azure, AWS), and DevOps tools (Kubernetes, Docker, CI/CD).
- Proven experience in leading global AI engineering teams, driving product innovation, and ensuring operational excellence.
- Track record of delivering enterprise-grade AI solutions with security, scalability, and regulatory compliance.
- AI solutions with compliance, security, and performance at scale.
Optional Skills:
- Experience in AI-powered digital transformation across BFSI, healthcare, real estate, manufacturing, supply chain, education, retail, and cybersecurity.
- Published research, patents, or contributions to AI innovation and technology advancements.
- Familiarity with regulatory frameworks including GDPR, HIPAA, BFSI compliance, and AI ethics governance.
- Experience in high-growth AI startups or global enterprises, leading AI technology initiatives at scale.
Key Performance Indicators (KPIs):
Technology Product Performance
- AI Model Performance: Maintain 90%+ accuracy in AI/ML models deployed in production.
- Cloud Optimization: Reduce AI processing costs by 30% through cloud optimization strategies.
- System Uptime: Maintain 99.99% availability for AI-powered SaaS platforms.
Engineering Innovation Success
- AI Model Deployment Speed: Reduce time-to-market for AI models by 50% year-over-year.
- Code Quality Security: Maintain zero critical vulnerabilities in AI applications.
- AI Innovation Index: Launch three or more major AI features per year.
Business Market Impact
- AI Adoption Rate: Increase enterprise AI adoption by 50% year-over-year.
- Revenue Growth Contribution: AI-driven solutions contribute to 25%+ of new enterprise deals.
- Market Expansion: Expand iTCart s AI solutions across three or more new global markets annually.
Compliance Security
- Regulatory Compliance: Ensure 100% adherence to BFSI, healthcare, and global regulatory standards.
- Responsible AI: Implement AI governance frameworks for fairness, bias detection, and ethical AI practices.
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