\\\\Description\\\\ At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. \\\\How will you make an impact in this role?\\\\ The Staff Engineer will drive the creation of data driven capabilities and intelligent frameworks, including GenAI, that deliver measurable business value and ROI. This role partners across the enterprise to identify high impact modernization opportunities and to design scalable, reusable data and AI platform solutions that influence the firms long-term technical direction. As part of an AI Lab oriented environment, the Staff Engineer will also lead R&D efforts, staying ahead of state-of-the-art AI technologies, evaluating their enterprise applicability, and guiding teams from experimentation to production ready architectures. \\\\Core Responsibilities:\\\\ \\\\Enterprise Cloud Data Architecture & Platform Engineering: -\\\\ \\+ Lead the hands-on design and implementation of scalable, secure, and resilient cloud-based data platforms supporting enterprise-scale workloads. \\+ Define and enforce cloud data architecture standards, reusable patterns, and reference implementations aligned to enterprise architecture principles. \\+ Design distributed data processing frameworks and storage architectures optimized for performance, cost efficiency, and high availability. \\+ Conduct architecture reviews, validate solution designs, and actively guide engineering teams through implementation to ensure alignment with approved patterns. \\\\Data as a Service, Data Engineering Standards & Quality: -\\\\ \\+ Design and implement enterprise-grade data architectures that enables Data as a Service (DaaS) and Metrics as a Service ( MaaS) capabilities. \\+ Provide deep technical leadership in data modeling (conceptual, logical, physical) and scalable data engineering design.Partner directly with engineering teams to review pipelines, transformation logic, and orchestration frameworks to ensure high-quality, production-grade data assets. \\+ Drive reduction of technical debt by standardizing ingestion, transformation, and serving layer architectures across domains. \\\\Data Governance, Security & Compliance by Design: -\\\\ \\+ Embed enterprise data governance, privacy, encryption, and access control standards directly into platform architecture and engineering workflows. \\+ Partner closely with Information Security, Risk, and Compliance teams to ensure alignment with regulatory obligations and internal control frameworks. \\+ Ensure platforms maintain full lineage, audit trails, and monitoring capabilities to support risk transparency and operational accountability. \\+ Champion secure-by-design and compliant-by-design engineering practices across all data initiatives. \\\\AI & GenAI Platform Architecture, Innovation & Governance: -\\\\ \\+ Design and implement enterprise-grade data architectures that enable scalable AI and GenAI use cases within established governance, risk, and compliance guardrails. \\+ Lead hands-on prototyping and proof-of-concept initiatives to evaluate emerging AI and data technologies, assessing them against enterprise standards for scalability, security, cost efficiency, operational maturity, and integration feasibility. \\+ Guide engineering teams in integrating AI services into production data platforms with strong controls for data quality, traceability, model lifecycle management, and responsible AI practices. \\+ Translate AI Labs R&D outcomes into actionable architectural recommendations, reference patterns, and implementation roadmaps, driving disciplined experimentation, reuse of proven capabilities, and prevention of technology sprawl across the enterprise. \\\\Critical Skills & Experience\\\\ \\+ Deep expertise in cloud engineering and cloud-native architectures. \\+ Strong background in data engineering and data architecture at scale. \\+ Proven experience in database design, data modeling, and performance optimization. \\+ Solid understanding of data management principles, including data quality, lineage, and lifecycle management. \\+ Hands-on experience driving or influencing data governance practices in enterprise environments. \\+ Working knowledge of AI fundamentals and how data platforms enable ML and GenAI use cases. \\+ Expertise in Generative AI related technologies like Prompt engineering, Retrieval-Augmented Generation , embeddings, fine-tuning and model optimization. \\+ Experience with building AI agents & designing Multi-Agent Architectures. \\+ Experience implementing Responsible AI frameworks. \\+ Strong programming skills. \\\\Qualifications\\\\ We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: \\+ Competitive base salaries \\+ Bonus incentives \\+ Support for financial-well-being and retirement \\+ Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) \\+ Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need \\+ Generous paid parental leave policies (depending on your location) \\+ Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) \\+ Free and confidential counseling support through our Healthy Minds program \\+ Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations. \\\\Job:\\\\ Technology \\\\Primary Location:\\\\ India-Tamil Nadu-CHENNAI \\\\Schedule\\\\ Full-time \\\\Req ID:\\\\ 26002834

The role requires deep expertise in cloud engineering and cloud-native architectures, along with a strong background in data engineering and data architecture at scale. Proven experience in database design, data modeling, and performance optimization is necessary. A solid understanding of data management principles, including data quality, lineage, and lifecycle management, is essential. The candidate must have hands-on experience driving or influencing data governance practices in enterprise environments. Working knowledge of AI fundamentals and how data platforms enable ML and GenAI use cases is required. Expertise in Generative AI related technologies such as Prompt engineering, Retrieval-Augmented Generation, embeddings, fine-tuning, and model optimization is also a requirement. Experience with building AI agents and designing Multi-Agent Architectures, as well as implementing Responsible AI frameworks, is needed. Strong programming skills are also a prerequisite.