Cognizant

AIA - Principal Architect

Cognizant • $130K — $180K *
Philadelphia, PA 19120In-Person
Enterprise Technology
5 - 7 years of experience
Reposted 5 days ago
Job Overview by Ladders

Qualifications

  • Extensive experience in delivering large-scale solutions on major cloud platforms, emphasizing infrastructure as code and secure multi-account architectures.
  • Deep practical expertise in designing and operating machine learning systems, including all stages from data preparation to performance monitoring.
  • Advanced knowledge of AI concepts like supervised and unsupervised learning, enabling realistic solutions for varied business needs.
  • Proficiency with cloud template authoring and modular design for infrastructure resources to support automation and continuous delivery.
  • Strong communication skills for elucidating complex architecture decisions to both technical and non-technical stakeholders.
  • Solid understanding of security and ethical principles in AI, ensuring architectures comply with regulations.

Responsibilities

  • Drive end-to-end architecture for AI and ML solutions addressing complex business challenges and creating measurable outcomes.
  • Define reference architectures and design patterns for cloud-native data pipelines and machine learning platforms.
  • Design secure multi-account cloud environments with infrastructure as code practices for compliant resource provisioning.
  • Collaborate with data scientists and engineers to translate use cases into effective technical designs.
  • Guide the integration of cloud ML services for resilient pipelines throughout the model lifecycle.
  • Oversee non-functional architecture concerns, embedding resilience and compliance into designs.
  • Conduct architecture reviews, providing recommendations to align with enterprise strategy and risk management.

Benefits

  • Opportunity to work with a multinational organization on cutting-edge AI and ML technologies.
  • Flexible hybrid work environment facilitating collaboration across teams and geographies.
  • Focus on driving measurable value for customers and society through innovative solutions.
  • Mentorship opportunities for team development and professional growth in architectural best practices.
  • Engagement with emerging technologies and their societal impacts, fostering a culture of continuous learning.
Full Job Description
Job Summary

Serve as a principal architect designing advanced artificial intelligence and machine learning solutions on cloud infrastructure for a multinational organization using cloud native services and automation to deliver secure scalable and resilient platforms that create measurable value for customers and society while guiding teams through complex transformation initiatives in a hybrid work environment.

Responsibilities
  • Drive end to end architecture for artificial intelligence and machine learning solutions on cloud infrastructure that address complex business challenges and create measurable outcomes for customers and communities through reliable and scalable digital products.
  • Define reference architectures and reusable design patterns for cloud native data pipelines and machine learning platforms that enable rapid experimentation robust model deployment and consistent governance across multiple product lines.
  • Design secure multi account cloud environments using infrastructure as code practices with cloud template automation to ensure repeatable compliant and auditable provisioning of networking compute storage and data services.
  • Collaborate with data scientists engineers and product partners to translate analytical use cases into pragmatic technical designs that balance innovation performance cost efficiency and operational simplicity.
  • Guide the selection configuration and integration of cloud machine learning services including model training feature storage orchestration and monitoring to build resilient pipelines from data ingestion through model lifecycle management.
  • Oversee non functional architecture concerns such as resilience reliability observability privacy and regulatory compliance by embedding these controls into blueprints guardrails and automated validation checks from the start.
  • Conduct architecture reviews and technical deep dives for critical initiatives providing structured recommendations that reduce risk improve system quality and align with enterprise strategy and external regulatory expectations.
  • Mentor engineering and data teams on architectural best practices for artificial intelligence workloads including model deployment strategies data partitioning approaches cost optimization techniques and automation driven operations.
  • Partner with cybersecurity and risk stakeholders to design identity access and data protection models that safeguard sensitive information used by artificial intelligence solutions while preserving usability and analytical agility.
  • Create clear architecture documentation including diagrams decision records and transition roadmaps that enable shared understanding across engineering operations product and senior stakeholder communities.
  • Evaluate emerging technologies in artificial intelligence machine learning and cloud services by running targeted proofs of concept and providing objective guidance on adoption timing integration strategy and potential societal impact.
  • Optimize platform performance and cost by analyzing usage telemetry tuning resource configurations and recommending architecture changes that improve efficiency without compromising resilience or customer experience.
  • Support hybrid ways of working by enabling collaboration ready architectures standardized templates and automated environments that teams can use consistently regardless of physical location or time zone.


Qualifications
  • Demonstrate extensive experience delivering large scale solutions on major cloud platforms with strong focus on infrastructure as code automation cloud networking and secure multi account architectures.
  • Bring deep practical expertise in designing and operating machine learning systems including data preparation feature management model training model deployment and ongoing performance monitoring in production contexts.
  • Apply advanced knowledge of artificial intelligence concepts such as supervised learning unsupervised learning and model evaluation to frame realistic solution options and trade offs for diverse business domains.
  • Show proficiency with cloud template authoring tools configuration strategies and modular design approaches that support reuse version control automated testing and continuous delivery of infrastructure resources.
  • Exhibit strong ability to communicate complex architectural decisions through concise documentation and structured storytelling that enables technical and non technical stakeholders to make informed decisions.
  • Display solid understanding of security data protection and responsible artificial intelligence principles ensuring that architectures follow regulatory expectations ethical guidelines and company policies.


Certifications Required

No.

About Cognizant

TriZetto is Powering Integrated Healthcare Management. With technology solutions touching more than half the U.S. population today, TriZetto is uniquely positioned to drive the convergence of core benefit administration, care management and constituent engagement. TriZetto provides premier information technology solutions that enable payers and other constituents in the healthcare supply chain to improve the coordination of benefits and care for healthcare consumers.

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Learn more about Cognizant
Size
340,400 employees
Market Cap
$28.7 billion
Industry
Information Technology
Net Income
$1.3 billion
Founded
1994
5 Year Trend
+6.5%
Revenue
$16.6 billion
NASDAQ
CTSH
* Ladders Estimates

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