The Role
Leads the architecture and production implementation of enterprise AI and machine learning solutions. Responsibilities include cloud-native infrastructure, AI security and governance, model monitoring, optimization, lifecycle management, Python API development, and cross-functional technical leadership. The role requires extensive experience designing scalable AI/ML architectures and deploying solutions across AWS, Azure, or Google Cloud.
Summary Generated by Built In
Summary
We are seeking a seasoned AI/ML Solution Architect to lead the design and implementation of sophisticated artificial intelligence systems within the IT Services sector. This pivotal role involves orchestrating end-to-end machine learning lifecycles, ensuring robust cloud infrastructure, and driving strategic technical decisions that align with business objectives. The ideal candidate will serve as a bridge between complex data science concepts and scalable production environments, delivering secure, high-performance AI solutions that leverage cutting-edge technologies and foster cross-functional innovation.
Responsibilities
- Design and oversee the architecture of comprehensive AI and machine learning solutions from conception to production deployment.
- Establish and enforce AI security protocols and governance frameworks to ensure data integrity and regulatory compliance.
- Architect scalable cloud-native environments utilizing AWS, Azure, or GCP AI services to support high-volume model inference and training.
- Develop strategies for continuous model monitoring, performance optimization, and lifecycle management in live production settings.
- Lead cross-functional initiatives, collaborating with engineering, product, and business teams to translate requirements into technical specifications.
- Engineer efficient Python-based APIs and integration layers to facilitate seamless interaction between AI models and existing enterprise systems.
- Drive the adoption of best practices for building resilient, scalable, and maintainable machine learning pipelines.
Requirements
Requirements:
- Possess 8 to 12 years of professional experience within the IT Services domain, with a significant focus on AI and machine learning technologies.
- Demonstrate deep expertise in designing end-to-end AI/ML architectures suitable for enterprise-scale applications.
- Proven proficiency in cloud platforms, specifically leveraging AI services across AWS, Microsoft Azure, or Google Cloud Platform.
- Strong command of Python programming and API development principles for model integration and service delivery.
- Extensive background in implementing model monitoring mechanisms and optimization techniques for production environments.
- Demonstrated ability to collaborate effectively across diverse teams to deliver complex technical solutions.
- Solid understanding of AI security standards and governance policies to mitigate risks and ensure ethical AI usage.
- Competitive compensation package offering up to ₹30 LPA.
Skills Required
- 8 to 12 years of professional experience in IT Services, with significant focus on AI and machine learning technologies
- Deep expertise designing end-to-end AI/ML architectures for enterprise-scale applications
- Proficiency with AWS, Microsoft Azure, or Google Cloud Platform AI services
- Strong Python programming and API development skills
- Extensive experience implementing model monitoring and optimization for production environments
- Ability to collaborate across diverse teams to deliver complex technical solutions
- Understanding of AI security standards and governance policies
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The Company
What We Do
Vrinda International is a Chandigarh-based recruitment and education consultancy connecting job seekers and employers through domestic and international IT and non-IT hiring. It also supports students with overseas university admissions, visa applications, education guidance, and test preparation for IELTS, PTE, and other programs. Its tech-enabled talent portal provides job matching and career pathways across India and global markets, alongside staffing partnerships.
