Company Overview :

Infosys is a global leader in next-generation digital services and consulting. With over four decades of experience in managing the systems and workings of global enterprises, the company steers clients through their digital journey by enabling them with an AI-powered core. Infosys operates across a vast spectrum of industries, including financial services, retail, manufacturing, and healthcare, leveraging its massive global footprint to deliver scalable, high-impact technology solutions to Fortune 500 companies.

Role Overview :

As a Principal Architect, you will serve as the technical authority for large-scale AI and ML initiatives, bridging the gap between complex data science models and robust production environments. You will collaborate with senior stakeholders, engineering leads, and data scientists to design resilient architectures that prioritize security, scalability, and operational excellence. Your work will directly influence how global enterprises deploy, monitor, and govern AI systems, ensuring that our clients maintain a competitive edge through secure and efficient AI infrastructure.

Key Responsibilities :

- Design and implement end-to-end MLOps and AIOps frameworks to streamline the lifecycle of machine learning models from experimentation to production.

- Define security architectures for AI/ML pipelines, ensuring data privacy, compliance, and protection against adversarial threats in cloud-native environments.

- Lead the architectural strategy for large-scale data engineering and ML infrastructure, enabling high-performance model training and inference.

- Partner with cross-functional teams to integrate Kubernetes-based orchestration into existing enterprise ecosystems, enhancing deployment velocity and system reliability.

- Provide technical leadership and mentorship to engineering teams, driving best practices in AI architecture and cloud computing to meet evolving business requirements.

Enterprise Competencies :

- Learning Agility :

1. Demonstrates the ability to rapidly acquire and apply technical expertise in AI, machine learning, and data platforms; embraces evolving toolsets, programming languages, and frameworks with a growth mindset.

2. Stays current with industry trends, regulatory developments, and emerging architecture patterns across cloud, AI, and enterprise platforms.

- Customer Centricity :

1. Puts enterprise and end-user needs at the center of architectural decisions; ensures solutions are reliable, compliant, and aligned with business objectives.

2. Communicates complex technology strategy effectively to executive stakeholders, industry partners, and customers, building trust through transparency and expertise.

- Tenacity / Persistence :

1. Guides technologists through rapidly changing environments, removing impediments and driving architectural decisions with conviction even in the face of ambiguity.

2. Demonstrates persistence in aligning enterprise technology vision with investment processes and delivering high-quality outcomes across large-scale, complex programs.

Required Qualifications :

- 12+ years of working experience in data intensive applications or data engineering.

- Experience implementing large-scale technological enhancements and/or pivots, including pilot implementation and analysis.

- Excellent understanding of AI/ML patterns and techniques.

- Excellent understanding of DevOps.

- Understanding of python and at least one other programming language.

- Experience working with IT infrastructure and cloud development.

- Experience with APIs.

- Experience designing highly available and resilient solutions, automation, identify opportunity of performance improvements.

- A bachelors degree or foreign equivalent in computer science or a related field.

- Experience in 2 or 3 of the following technology areas : Infrastructure, Security, DevOps, Application Development, database technologies, cloud computing.

Desired Qualifications :

- Working experience in the financial services industry.

- Executive speaking and presentation skills : formal presentations, white-boarding, large and small group presentations.

Education and Certifications :

- Required : Bachelor's degree.

- Preferred : Degree in Software Engineering, Computer Science, Engineering, Mathematics or related discipline.