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Salary
≈ $14k – $32k per year (Estimated)
Location
Hybrid (Bengaluru, India)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 17, 2026. Cognizant scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Cognizant is an American information technology services and consulting company founded in 1994 as an in-house technology unit of Dun and Bradstreet in Chennai, India, and headquartered in Teaneck, New Jersey. It builds, integrates and operates software and infrastructure for large enterprises, with particularly deep positions in healthcare, financial services, insurance and life sciences, delivered by a global workforce of more than three hundred thousand people concentrated in India. Listed on Nasdaq, the company competes with the large Indian and global systems integrators and has reoriented its offerings around cloud migration, data platforms and AI-assisted engineering.

Job Summary

This hybrid role is for a senior full stack engineer with eight to twelve years of experience who will design build and optimize automated insight solutions using artificial intelligence across card and payment platforms. The role focuses on secure scalable applications that turn complex data into meaningful actions while aligning to enterprise engineering standards and improving customer outcomes.

Responsibilities

  • Design and implement scalable full stack applications that deliver automated insights from complex data sets and provide responsive experiences for card and payment users.
  • Develop robust backend services that orchestrate data pipelines apply artificial intelligence models and expose secure interfaces for insight driven features.
  • Build intuitive and accessible frontend interfaces that visualize automated insights clearly and enable users to act quickly on data driven recommendations.
  • Optimize application performance by tuning queries refactoring services and improving client side interactions to support low latency insight delivery.
  • Collaborate with data science teams to productionize artificial intelligence models and translate analytical outputs into reliable full stack solutions.
  • Create reusable components and shared libraries that standardize automated insight capabilities across multiple products and business lines.
  • Implement secure coding practices and compliance controls tailored to payment data so that automated insight features protect sensitive information.
  • Integrate systems with card and payment gateways or related services to ensure automated insights are grounded in accurate and timely transaction data.
  • Develop automated tests and continuous integration workflows that validate artificial intelligence pipelines and full stack functionality end to end.
  • Monitor production environments using observability tools and address incidents proactively so that automated insight services remain highly available.
  • Document system designs technical decisions and operational runbooks so that engineering teams can maintain and extend automated insight solutions efficiently.
  • Mentor colleagues by sharing best practices in full stack engineering and artificial intelligence integration to uplift overall team capability and delivery quality.
  • Align work with organisational goals by prioritising features that improve customer trust financial inclusion and responsible use of artificial intelligence in payment experiences.

Qualifications

  • Showcase eight to twelve years of full stack engineering experience with strong proficiency in building secure and scalable web applications end to end.
  • Demonstrate hands on experience implementing automated insight solutions using artificial intelligence or machine learning techniques integrated into production systems.
  • Exhibit proficiency with modern frontend frameworks and backend technologies along with solid understanding of relational or nonrelational databases.
  • Display familiarity with card and payment domain concepts such as transaction flows authorisation processes and risk controls even if experience is limited.
  • Apply working knowledge of secure coding standards data privacy requirements and regulatory expectations relevant to financial technology applications.
  • Utilise experience with continuous integration tools automated testing frameworks and version control to maintain high quality release cycles.
  • Communicate effectively with cross functional partners including product design and data experts to translate requirements into implemented features.
  • Adapt quickly to evolving artificial intelligence tools and frameworks by engaging in continuous learning and experimentation in a structured manner.

Certifications Required

Recommended certifications include a cloud associate level credential and an artificial intelligence or machine learning engineering certification.

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