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Salary
$28k – $64k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 9+ years exp
Overview
Company
Impact
Profile match
American Express is a New York financial services company founded in 1850 as an express freight business that became a payments network and card issuer. Unlike the four-party networks it competes with, it issues most of its own cards and operates its own network, which lets it earn merchant discount revenue as well as interest and annual fees, and supports a premium rewards proposition built on travel and lounge access. Its business spans consumer and small business cards, corporate payments, merchant acquiring and travel services, and it is a component of the Dow Jones Industrial Average.

The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.

A Sr Software Engineer I (Automation and AI) designs, develops, and implements intelligent automation and AI-powered solutions, integrates enterprise systems and workflows, ensures adherence to engineering and governance best practices, mentors engineers and collaborates with cross-functional teams to improve operational efficiency, scalability, and user experience.

  • Mentors junior Engineers and cross-functional teams, fostering a culture of innovation, collaboration, and continuous learning.
  • Provides technical guidance and support to engineers on automation, AI technologies, and enterprise integration best practices.
  • Leads the design, development, testing, deployment, and maintenance of intelligent automation solutions, AI-powered applications, and workflows.
  • Oversees the implementation and optimization of automation platforms, APIs, and enterprise integrations to meet evolving business requirements.
  • Develops and maintains automated testing, validation, and evaluation frameworks to ensure the reliability, accuracy, and performance of solutions.
  • Establishes and enforces engineering standards, coding practices, governance, security, and responsible AI principles across automation initiatives.
  • Monitors the performance, scalability, and reliability of automation workflows and applications, implementing improvements to optimize efficiency and user experience.
  • Analyzes complex technical and business challenges and develops solutions to improve productivity, operational excellence, and customer outcomes.
  • Collaborates with architects, product managers, data scientists, security teams, and business stakeholders to ensure seamless integration, deployment, and adoption of software solutions.
  • Partners with product and business teams to identify automation and AI opportunities, translating business needs into scalable, secure, and maintainable technology solutions.
  • Designs and develops reusable components, to accelerate solution delivery and promote standardization across the organization.
  • Evaluates emerging technologies, tools, and frameworks, recommending and implementing solutions that enhance engineering capabilities and business value.
  • Ensures compliance with enterprise architecture, security, risk, privacy, and regulatory requirements throughout the software solution lifecycle.
  • Drives continuous improvement by leveraging metrics, monitoring, and feedback to enhance the effectiveness, adoption, and business impact of application capabilities.

Education Qualifications:

  • Bachelor’s degree in Computer Science, Computer Engineering, and/or comparable experience; advanced degree preferred
  • Knowledge of distributed (multi-tiered) systems, algorithms, APIs, NoSQL, and relational databases.
  • Knowledge of the core tools used in planning, analyzing, designing, developing, testing, deploying, and maintaining software applications.
  • Knowledge of software engineering principles, object-oriented design, data structures, design patterns, and application architecture.
  • Knowledge of automation frameworks, workflow orchestration, and enterprise integration patterns.
  • Knowledge of AI application development concepts, including large language models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and AI-assisted development practices.
  • Knowledge of cloud platforms, CI/CD pipelines, DevOps practices, and application monitoring.

Work Experience:

  • 9+ years of experience in application design, software development, automated testing, and software lifecycle management.
  • Experience in object-oriented design and development using Java and/or Python programming languages.
  • Experience with distributed (multi-tiered) systems, algorithms, APIs, and relational and NoSQL databases.
  • Experience with Agile software development methodologies and practices such as Scrum, Kanban, iterative development, and user stories.
  • Experience implementing automation solutions to improve software delivery, operational efficiency, and business processes.
  • Experience integrating applications and services using REST APIs, messaging technologies, and enterprise integration patterns.
  • Experience leveraging AI technologies, including LLMs, AI-powered development tools, or intelligent automation solutions, to enhance software development and business capabilities.
  • Experience in automated testing and documentation (e.g., unit, integration, functional, performance, and regression testing).
  • Experience deploying, monitoring, and optimizing applications in cloud environments using CI/CD and DevOps practices.
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