Lead Software Engineer
Posted Updated
- At Mastercard Services, you will serve as a senior technical leader and hands-on engineer for BE&O’s next-generation experimentation and analytics platform. As a Lead Software Engineer, you will lead through technical influence, architectural judgment, and execution excellence to help modernize our platform and deliver scalable, secure, cloud-native capabilities for global business users
- Design, develop, and deploy AI-powered products, intelligent agents, and agentic workflows utilizing Large Language Models (LLMs), retrieval systems, orchestration frameworks, tool-calling patterns, and context-aware workflows
- Architect and implement advanced agentic systems incorporating planning, reasoning loops, memory management, grounding, evaluation frameworks, safety mechanisms, and human-in-the-loop controls
- Lead the transition of AI solutions from proof-of-concept to production by establishing best practices for reliability, observability, performance, security, governance, and cost optimization
- Develop scalable AI applications and developer productivity solutions using modern AI frameworks, SDKs, and orchestration platforms
- Serve as a hands-on technical contributor, designing, coding, testing, debugging, and delivering production-quality software across the full engineering lifecycle
- Build and evolve scalable services, APIs, and analytical capabilities using modern engineering practices, cloud platforms, and data technologies such as AWS, Azure, Databricks, Spark/PySpark, Python, Java and related frameworks
- Partner closely with product managers, engineering teams, architects, data scientists, QA, security, and operations teams to translate business and functional requirements into robust technical solutions
- Coordinate and lead technical execution across globally distributed engineering teams, ensuring alignment across regions, time zones, dependencies, design decisions, and delivery milestones
- Drive architecture and design reviews, code reviews, technical decision-making, and engineering tradeoff discussions to ensure solutions are secure, resilient, observable, performant, maintainable, and aligned with enterprise standards
- Drive engineering excellence through CI/CD automation, DevSecOps practices, automated testing, and AI-assisted software development workflows
- Establish reusable platforms, frameworks, accelerators, and engineering capabilities that improve developer productivity and accelerate solution delivery across teams
- Identify opportunities to improve platform scalability, reliability, developer productivity, operational readiness, and speed of delivery through modernization, automation, reusable patterns, and engineering best practices
- Provide technical mentorship to junior and mid-level engineers through design guidance, code review, pairing, knowledge sharing, and modeling strong engineering judgment
- Navigate ambiguity in complex initiatives by clarifying technical direction, decomposing large problems, identifying risks, and driving alignment across stakeholders
- Champion a culture of engineering excellence, continuous improvement, ownership, collaboration, and high-quality delivery across the team and partner organizations
- Proven experience building and delivering AI-powered applications, intelligent agents, or generative AI solutions in enterprise environments
- Strong hands-on experience designing and building distributed systems, microservices, RESTful APIs, and cloud-native applications
- 8+ years of software engineering experience delivering scalable, high-performance, and reliable software in an agile environment
- Strong understanding of agentic AI architectures, including workflow orchestration, reasoning frameworks, memory systems, grounding techniques, evaluation methodologies, and safety controls
- Hands-on experience with modern AI frameworks, SDKs, orchestration platforms, vector databases, retrieval systems, and agent development tooling
- Strong experience with data-intensive applications and analytics platforms; experience with Databricks, Spark, or PySpark is highly desirable