Senior Software Engineer - Backend/Platform Agentic AI
$132,000–$212,000 year
On-site · Arlington, Virginia, United States
Job Summary
Senior Software Engineer responsible for end-to-end development of agentic AI systems within Mastercard's Portfolio Intelligence platform. Lead architecture and implementation of AI-enabled services in Java and Python in a multi-tenant, customer-facing environment; orchestrate tool calling, context engineering, retrieval, and streaming responses; define integration strategies and governance standards; build production-grade AI infrastructure (prompt management, evaluation frameworks, guardrails, observability, cost/token telemetry); collaborate with platform teams, vendors, and product teams to deliver integrated end-to-end solutions; supervise code quality, testing, deployment, and operational readiness; provide hands-on technical leadership through design reviews, pairing, and mentorship; ensure compliance with security and Responsible AI standards; drive metrics like task success rate, latency, and human intervention rate. All About You lists required skills in Java, Python, agentic/LLM systems, CI/CD, cloud, observability, and governance. Nice-to-have includes multi-tenant architectures, Databricks/Snowflake, vector databases, Kubernetes, and knowledge of AI governance in regulated environments.
Required Qualifications
- Expertise with Java (Spring Boot, microservices) for backend services
- 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
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