Principal software Engineer

Principal software Engineer

[GC1.1]

Overview

We are seeking a hands-on Principal Forward Deployed Engineer to accelerate delivery across Mastercard Services. Modeled on the forward deployed engineering role that leading technology companies embed alongside their most important customers, this position turns that model inward. You will deploy into Services programs as an internal partner who writes production code, unblocks delivery, and puts AI to work in how we build. Reporting to the SVP of Developer Enablement within the Services Enablement Transformation (SET) organization, you will move to wherever the need is greatest, adding senior engineering capacity during critical spikes, accelerating roadmaps, and helping teams adopt modern, AI-first practices.

Role

The Principal Forward Deployed Engineer is a senior individual contributor who deploys into Services teams to deliver working software and durable capability. Engagements are deliberately fluid. Some last few weeks to help a team ship a critical feature or clear a bottleneck, while others run longer to stand up a capability a program is missing. In every engagement you write production code, pair with the teams engineers, put AI to work in how they build, and leave the team faster and more capable than you found it.

Deliver Where Its Needed Most

- Embed directly into Services product and engineering teams, writing production-quality code and shipping features alongside them.

- Provide surge engineering capacity during critical delivery spikes, helping programs accelerate roadmaps and hit high-stakes milestones without permanently expanding headcount.

- Diagnose and clear technical bottlenecks across architecture, performance, integration, tooling, and delivery process.

- Fill short-term gaps with deep expertise, standing up new capabilities, and transferring them cleanly to the product team.

- Move fluidly across Services as priorities shift, scoping each engagement with program leaders and Developer Enablement so effort lands where it matters most.

Engineer AI Into How Services Builds

- Design and deploy production-grade AI solutions such as assistants, agents, and multi-agent workflows that solve real problems inside Services programs.

- Apply modern AI engineering practices, including LLMs, RAG, and agent frameworks, along with the evaluation, observability, and governance needed to run them safely in production.

- Mature AI adoption across the software development lifecycle, including AI-assisted coding, testing, code review, and release.

- Evaluate emerging AI capabilities and turn them into reusable patterns and reference implementations that Services teams can adopt.

Upskill Teams and Scale What Works

- Coach teams on AI-first ways of working through hands-on delivery, including pairing, prompt engineering, and agent design.

- Leave every team more self-sufficient than you found it, emphasizing documentation and knowledge transfer, so programs do not stay dependent on you.

- Carry patterns, friction points, and reusable solutions back from the field to inform Services-wide enablement, tooling, and golden paths.

- Partner with enterprise architecture, platform, and developer enablement teams so what you deliver aligns with Mastercard standards and scales beyond a single program.

Your impact shows up in the teams you leave behind. The programs you support ship faster, more of Services builds with AI because you showed them how, and the engineers you coach can keep building after you move on. You also leave behind reusable AI patterns and reference implementations that other teams can pick up and run with.

All About You

The ideal candidate is a seasoned, hands-on engineer who thrives on variety, moves fast, and measures success by outcomes delivered and teams left stronger. Specifically, you bring:

- Extensive hands-on software engineering experience at a Principal or Senior Principal Engineer level, with a track record of personal shipping complex, production-grade systems.

- Advanced experience overseeing containerization and orchestration architectures (Docker, Kubernetes, Service Meshes) across hyper-scale cloud environments.

- Deep, current experience building with AI and Agentic solutions, including LLMs, agent frameworks, RAG, and orchestration patterns, and a track record of deploying AI solutions that deliver measurable outcomes.

- Exceptional technical breadth, becoming productive quickly across unfamiliar languages, frameworks, domains, and codebases.

- Deep fluency in modern development practices, including CI/CD, automation, cloud-native architecture, testing, and developer tooling.

- Practical, current command of AI across the software development lifecycle, and the ability to coach engineering teams in adopting it effectively.

- A working grasp of responsible AI, governance, and production monitoring for AI systems.

- A proven ability to parachute into unfamiliar teams, build trust fast, and deliver measurable outcomes under time pressure.

- A pragmatic, delivery-focused mindset that prioritizes shipping, working software and teaching by doing.

- Strong communication and influencing skills that earn credibility with engineers and program leaders alike.

- Comfort with ambiguity, frequent context-switching, and self-directed scoping where you can add the most value.

- Hands-on experience with GitHub Copilot, Claude Code, Copilot Studio, Azure AI, or equivalent AI development platform preferred.

- Demonstrated passion for simplification, innovation, and enabling speed and quality across the organization.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.