Senior Software Engineer, Developer Experience (DevEx)

About Us 

MarketAxess is on a journey to digitally transform one of the world’s largest financial markets, enabling the shift from analog, phone-based trading to a fully electronic marketplace. Why does this matter? Because our platform makes trading fixed-income more accessible, ultimately improving transparency, efficiency, and competition in the marketplace. Changing the way an established industry transacts is no easy feat. There will be twists and turns, because no one’s ever done this before. But now, more than 2,000 clients around the world rely on our solutions, and that number is only expected to grow in the years ahead. We know where we’re going. How we get there is up to us. Join us and help Take Us There. 

The Role

We are seeking an experienced Senior Software Engineer to join our Developer Experience (DevEx) team.  

This role focuses on designing and implementing AI‑enhanced developer platforms and tools that help streamline, automate, and optimize the work of engineers across our trading systems. You’ll build intelligent systems that improve productivity, code quality, and operational resilience — enabling faster, safer, and more efficient delivery of products and trading software. 

DevEx builds and maintains the internal platforms, tooling, and paved paths that help product teams ship safely and quickly by improving build and deployment velocity, reliability, quality, security, and overall developer satisfaction—including how we responsibly adopt and operationalize AI across the software development lifecycle. 

In this role, you’ll partner with engineers, security, and product stakeholders to design, build, and operate the systems developers use every day (CI/CD, developer portals, templates, observability, testing, and golden paths).  

A key focus will be enabling AI-assisted engineering at scale—rolling out developer tools, reusable workflows, and evaluation/telemetry so teams can use AI effectively with clear guardrails (security, privacy, compliance) and measurable outcomes. You’ll also help drive adoption through documentation, enablement, pragmatic standards, and metrics—mentoring others and raising the bar for engineering practices across the company. 

How You'll Help Take Us There

• Design, develop, and maintain internal developer platforms, tooling, and frameworks with integrated AI capabilities (e.g., intelligent code review, documentation generation, test‑automation assistants).
• Innovate around how AI and machine learning can improve the developer experience — from smarter debugging to predictive system reliability tools.
• Collaborate with product, platform, and infrastructure teams to optimize developer workflows and automate routine engineering tasks.
• Implement and maintain CI/CD pipelines, build systems, and developer services that leverage AI/ML insights for faster feedback and improved performance.
• Champion AI‑driven observability and anomaly detection to pre‑empt deployment or infrastructure issues.
• Work closely with data science and platform engineering teams to embed model‑informed automation into developer processes.
• Mentor engineers on applying generative AI tools effectively and responsibly across the SDLC.
• Ensure all AI‑based tools comply with the firm’s security, governance, and regulatory standards. 

What We’re Looking for  

• 7+ years of software engineering experience, ideally within financial services or other high‑performance, low‑latency domains.
• Proficiency in Python, Java, C++, or Go, with a strong background in building internal platform tools and automation.
• Experience developing or deploying AI‑assisted developer tools, such as LLM‑based code assistants, intelligent CI/CD systems, or automated documentation/testing frameworks.
• Deep understanding of CI/CD pipelines, infrastructure‑as‑code (Terraform, Ansible), and container platforms (Docker, Kubernetes).
• Expertise in software build systems, dependency management, and continuous integration best practices.
• Familiarity with machine learning operations (MLOps) concepts or AI model lifecycle management.
• Strong communication skills and the ability to collaborate across teams and technical domains.
• Background