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Senior Software Engineer - Backend/Platform Agentic AIDynamic Yield • United States
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Senior Software Engineer - Backend/Platform Agentic AI

Dynamic Yield
  • US
    United States
  • US
    United States
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Über

Senior Software Engineer - Backend/Platform Agentic AI
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. The Portfolio Intelligence (PI) program within Mastercard's Business & Market Insights (B&MI) division delivers analytics products that help financial institutions understand and grow their card portfolios. We are building a first-party AI platform that brings agentic, conversational, and generative AI capabilities directly into our products; powering features like natural-language analytics, automated report summaries, and personalized dashboard experiences for thousands of customers worldwide. This is a senior individual contributor role with significant technical ownership. You will drive hands-on delivery of production AI systems, make key implementation decisions, and serve as a leading contributor shaping how AI capabilities are built and operated within Portfolio Intelligence. You'll partner closely with product, shared AI infrastructure teams, and vendor partners to take AI solutions from architecture through production at enterprise scale. About the Role: Lead end-to-end development of agentic AI systems from design through production. This includes orchestration, tool calling, context engineering, retrieval, and streaming responses. Define technical direction for AI capabilities within the PI platform, driving architecture, design patterns, and integration strategies Build and operate AI-enabled services in Java and Python within a multi-tenant, customer-facing environment, ensuring scalability, reliability, and strict data isolation Design and implement production-grade AI infrastructure, including prompt management, evaluation frameworks, guardrails, observability, and cost/token telemetry Partner with platform teams (agent frameworks, LLM gateway), vendors (semantic data layer), and product teams to deliver integrated, end-to-end solutions Establish and enforce engineering standards for AI development—code quality, testing, deployment, and operational readiness Provide hands-on technical leadership through design reviews, code reviews, pairing, and mentorship Ensure AI solutions meet Mastercard governance, security, and Responsible AI standards in a regulated environment Drive continuous improvement by defining and tracking metrics (task success rate, latency, cost per interaction, human intervention rate) and expanding evaluation coverage All About You: Proven experience productionizing AI/ML systems, delivering reliable, scalable services used in real-world environments Strong engineering expertise in Java (Spring Boot, microservices) and Python (AI/ML tooling, scripting, services) Deep experience building agentic or LLM-based systems: tool/function calling, RAG, context management, prompt engineering, and orchestration Demonstrated technical leadership through design reviews, mentoring, and raising engineering standards without formal people management Strong operational ownership mindset, including observability, incident response, and service reliability Comfortable operating in ambiguity and making pragmatic architectural decisions Clear communicator able to translate complex technical concepts, present tradeoffs, and produce actionable design documentation Effective collaborator across teams, vendors, and distributed organizations Required skills to be considered: Expertise with Java for backend services (Spring Boot, microservices) Fluent in Python for AI/ML development (agentic frameworks, scripting, integrations) Hands-on experience building LLM-powered production systems (API integration, prompt management, streaming, error handling, cost management) Experience with agentic frameworks (LangGraph, LangChain, or similar), RAG pipelines, or AI orchestration systems Proven ability to design scalable distributed systems with strong observability (logging, metrics, tracing, alerting) Experience with CI/CD and modern SDLC practices (automated testing, quality gates, deployment automation) Cloud experience (AWS or Azure), including managed AI/ML services Technical leadership in design reviews, mentoring, and setting engineering standards Solid backend/software engineering experience with ownership of distributed systems in production Nice-to-have skills: Experience with multi-tenant architectures and customer data isolation Familiarity with AI evaluation frameworks (agent evaluation, prompt regression testing, output quality metrics) Experience with Databricks, Snowflake, or similar data platforms Knowledge of vector databases, semantic search, knowledge graphs, and MCP Exposure to analytics platforms, BI tools, or semantic data layers Understanding of AI governance and Responsible AI practices in regulated environments Experience with Kubernetes, container orchestration, and infrastructure-as-code Background in financial services or payments Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Corporate Security Responsibility: Abide by Mastercard's security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines. In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. Pay Ranges: Arlington, Virginia: $132,000 - $212,000 USD
  • United States

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