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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - Backend/Platform Agentic AI - **Company:** Mastercard - **Location:** Arlington, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Adobe InDesign, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Automation of Tests, Microsoft Azure, Cloud Computing, Software Quality, Code Review, Continuous Integration, Customer Data Management, Software Design Patterns, Distributed Systems, Graph Database, Python (Programming Language), Systems Development Life Cycle, Regression Testing, Azure Machine Learning, Search Technologies, Software Engineering, Data Streaming, Systems Integration, AI Infrastructure, Data Logging, Scripting, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Spring-boot, Backend, Data Layers, AI Platforms, Kubernetes, Deployment Automation, Data Management, Machine Learning Operations, Virtual Agents, Databricks, Microservices - **Published:** August 9, 2026 - **Apply:** https://www.wayup.com/i-j-Senior-Software-Engineer-Backend-Platform-Agentic-AI-Mastercard-456308107762415/ ## About the Role * 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 ## Description 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 ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [JavaScript? No. Java Scripts! - Scripting with Java](https://www.wearedevelopers.com/videos/2094-javascript-no-java-scripts-scripting-with-java) - [The Missing Layer Between Enterprise Data and AI Agents](https://www.wearedevelopers.com/videos/100286-the-missing-layer-between-enterprise-data-and-ai-agents) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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