We are fueled by a moral imperative to advance mankind, and it all begins with our people, our product, and our purpose. Passion isn't something we turn on and off; it's woven into everything we do. If you thrive in high-challenge environments, are inspired by exceptional teammates, and are driven to grow beyond what you thought possible, MX is where you belong.

Come build the future with us. Join an award-winning company that isn't just shaping the financial industry, but transforming it in ways that create meaningful, lasting impact for millions of people.

Job Responsibilities

Build AI Developer Platforms and integration across SDLC: Design and build core AI developer platforms, like an LLM Gateway for standardized LLM access (routing, caching, observability, cost control), and integrate AI features (code generation, reviews, testing, debugging, documentation) across the SDLC.
Enable Agentic Systems: Build frameworks and orchestration layers to enable developers to create, deploy, and operate agent-based workflows (multi-step reasoning systems, Harnesses, tool-using agents, etc.)
Developer Experience & Productivity: Create intuitive abstractions, SDKs, and APIs that reduce friction and enable self-service adoption of AI capabilities across teams.
Scalable Platform Architecture: Architect and operate highly scalable, low-latency backend systems for high-throughput AI workloads, establishing best practices and golden paths for AI application development.
Observability & Governance: Implement monitoring, tracing, evaluation pipelines, and guardrails for AI systems, including prompt/version management, response quality tracking, and safety controls.
Cost & Performance Optimization: Design systems to optimize latency, throughput, and cost of LLM usage through techniques like caching, batching, and model routing strategies.
Collaboration: Work closely with platform, SRE, security, and product engineering teams to ensure AI capabilities are reliable, secure, and aligned with business needs.

Basic Qualifications

8+ years of experience in software engineering, backend development, or platform engineering.
Experience working with LLMs and Agentic AI systems, including Context engineering, Harness engineering, evaluation, or model integration.
Strong programming experience in languages such as Golang, Java, or Python.
Experience building and operating distributed systems and scalable backend services.
Experience designing and consuming APIs, microservices, and event-driven architectures.
Familiarity with CI/CD pipelines, testing frameworks, and developer toolings.
Strong debugging and problem-solving skills in production environments.

Preferred Qualifications

Experience building or integrating LLM Gateways, AI SDKs, or internal AI platforms.
Familiarity with agent frameworks (e.g., ADK, LangGraph, LangChain, or similar orchestration systems).
Experience designing multi-step workflows or automation systems using AI.
Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG) systems.
Experience with observability for AI systems, including prompt/version tracking and evaluation pipelines.
Understanding of cost optimization strategies for large-scale AI workloads.
Experience building developer platforms or internal tools that improve engineering productivity.
Exposure to SRE practices, including reliability, SLIs/SLOs, and incident response.
Hands-on experience with cloud platforms (AWS preferred) and containerized environments (Kubernetes).

Impact

Accelerate engineering velocity across MX by embedding AI into everyday engineering workflows.
Enable safe, scalable adoption of AI across the organization.
Reduce cognitive load on developers through intelligent automation and tooling.
Lay the foundation for autonomous and semi-autonomous engineering systems.

Senior Software Engineer II - Cloud Infra