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ABOUT YOUR ROLE We're hiring Senior Software Engineers to join our AI-native engineering team. You'll design, build, and operate production AI systems - including AI platform capabilities, agentic workflow infrastructure, and LLM-powered features that serve institutional financial clients. This is a hands-on individual contributor role for engineers who are deeply fluent in AI-native development and want to work at the intersection of applied AI and backend systems engineering. WHAT YOU'LL DO Build and Operate AI Systems - Design, build, and ship production-quality backend services, APIs, and AI platform components used across multiple engineering teams - Build and integrate LLM-powered systems such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, prompt/tool orchestration, and model observability - Improve the reliability, scalability, observability, and operational quality of production AI systems - Build internal tools, frameworks, automation, and documentation that improve developer productivity and AI capabilities - Participate in code reviews, design reviews, debugging, incident response, and operational support Drive Technical Excellence - Contribute to technical design for complex projects, including evaluating tradeoffs and proposing pragmatic implementation plans - Partner with product, design, and engineering teams to translate platform needs into well-designed technical solutions - Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle - Collaborate with Staff and senior engineers to establish reusable patterns and raise engineering standards Build with AI-Native Practices - Use agentic coding tools and LLM-assisted development as a primary part of your workflow this is how the entire team operates - Critically evaluate AI-generated code for correctness, edge cases, and regressions shipping quality output regardless of how it was produced - Contribute to the team's evolving practices around AI-accelerated development and testing QUALIFICATIONS Required - 5+ years of experience designing, building, and operating production software systems - Strong backend engineering experience with Python frameworks such as FastAPI, Flask, or Django - Experience building or integrating AI/LLM-powered systems in production - such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, or agentic workflows - Experience with relational/NoSQL databases, including schema design, query optimization, and data modeling - Experience with cloud-native technologies such as AWS, Docker, and Kubernetes - Solid understanding of CI/CD, observability, and operating services in production - Ability to break down complex technical problems and deliver pragmatic, maintainable solutions - Strong ownership mindset, with the ability to drive projects independently while collaborating effectively - Clear communication skills and the ability to explain technical tradeoffs to engineering and cross-functional partners - Hands-on experience with AI-native development tools (e.g., Cursor, Augment); demonstrated ability to embed AI-driven practices to accelerate velocity and code quality - Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases Preferred - Experience with document processing pipelines, structured extraction from unstructured documents, or vector stores - Familiarity with evaluation frameworks for LLM output quality (e.g., RAGAS, custom evals, human-in-the-loop review) - Background in financial services or fintech .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.