Staff Engineer, Developer Experience & Engineering Enablement

Staff Engineer, Developer Experience & Engineering Enablement

About DKatalis

DKatalis is built and backed by experienced and successful entrepreneurs, bankers, and investors in Singapore and Indonesia who have more than 30 years of financial domain experience and are from top-tier schools like Stanford, Cambridge London Business School, JNU with more than 30 years of building financial services/banking experience from Bank BTPN, Danamon, Citibank, McKinsey & Co, Northstar, Farallon Capital, and HSBC

About the role

We are looking for a Staff Engineer passionate about elevating developer experience (DevEx), engineering productivity, and software delivery workflows at scale.

In this role, you will lead the effort to design and build our next-generation software development ecosystem, pioneering the future of delivery by weaving practical AI capabilities directly into our development lifecycle. You will focus on creating internal tooling, automations, and self-service capabilities that empower global product teams to accelerate delivery and reduce operational friction. As a Staff Engineer, you will balance deep hands-on execution with cross-functional leadership, partnering closely with infrastructure and engineering teams to build highly automated, intelligent, and scalable workflows across the organization.

Role and Responsibilities:

• Build AI-Assisted Tooling: Architect, scale, and embed advanced AI-driven tools into daily workflows, including Contextual Engineering Assistants, automated code review agents, and intelligent incident response systems.
• Drive SDLC Automation: Build intelligent tooling across the SDLC to streamline code reviews, operational support, CI/CD pipelines, and developer self-service functions.
• Integrate Advanced Frameworks: Pragmatically orchestrate software patterns using Retrieval Augmented Generation (RAG), LLM tooling integrations, and the Model Context Protocol (MCP) ecosystem across GitLab, GitHub, and Slack (ChatOps).
• Technical Leadership: Establish tooling engineering standards, champion robust Kubernetes runtime architectures, and act as a force multiplier by mentoring engineers across teams.

Requirements:

• Practical AI Experience (Required): Proven track record of successfully implementing, shipping, and scaling production-grade applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agentic frameworks (e.g., MCP). This includes hands-on experience establishing evaluation, testing, and observability guardrails using modern LLM tooling (such as LangSmith, Phoenix, Braintrust, Langfuse, or Arize).
• Core Engineering Foundation: 10+ years of professional software engineering experience building distributed, cloud-native backend systems. Production proficiency in at least one backend language (Go, Java/Kotlin, or TypeScript/Node.js) alongside strong tooling capabilities (Python).
• Cloud & Automation Mastery: Deep understanding of software architecture, event-driven design, CI/CD pipelines, observability, and managing systems natively on Kubernetes.
• Developer Experience Application (Strong Plus): Direct experience or strong familiarity with Developer Experience (DevEx) design patterns, internal developer portals, or workflow orchestration engines (e.g., Temporal) is highly preferred.
• Systems Thinking & Influence: Demonstrated ability to simplify complex engineering processes, influence technical strategy across diverse teams, and successfully roll out enterprise-wide internal tooling.