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Summary We are hiring a Full Stack Engineer to build production applications, APIs, leveraging the existing application platform and frameworks, together with the cutting-edge AI framework (Agentic) and techniques. You will work on end-to-end features across React/TypeScript UI, backend APIs, IDP, and practice DevOps in a team environment. You will partner closely with teams across Multi-Asset Solutions, Investment Research, Investment Products, Accounting, Marketing, and Distribution to turn real investment and business needs into production-grade tools that improve decision-making, efficiency, and client outcomes. Who Will Thrive in This Role? This role is ideal for engineers who enjoy building AI powered software systems rather than developing standalone models. If your passion is designing and shipping modern applications and eco-system including related APIs with production grade AI elements, you will thrive here. You should be comfortable owning features end to end, including contributing to front end components when needed to improve usability, workflow design, and overall user experience. We value engineers who think in terms of complete solutions, not just backend services. Our emphasis is on building reliable, scalable applications. Key Responsibilities Design, develop, test, deploy, and maintain production-grade full stack applications using Python and/or React Build and enhance AI-enabled applications by integrating LLMs, agentic workflows, and MCP-based capabilities into enterprise software solutions Develop modern backend services and APIs that support business-critical workflows, automation, and secure application integration Collaborate with business and technology stakeholders to translate requirements into scalable solutions that improve decision-making and efficiency Contribute to intuitive, responsive, and user-friendly front-end experiences that improve usability and overall workflow design. Deploy and support cloud-native solutions on AWS using Docker, CI/CD pipelines, and Infrastructure as Code tools such as CloudFormation, Pulumi, or Terraform Write clean, maintainable, well-tested code and participate in code reviews, design discussions, and production support Optimize application performance, reliability, observability, and scalability while proactively troubleshooting issues in production Use AI-assisted development tools such as Claude Code to accelerate delivery and improve software quality Maintain technical documentation and contribute to reusable frameworks, engineering standards, and continuous improvement initiatives Key Behavioral Expectations Applies emerging AI/LLM capabilities pragmatically, with curiosity and good judgment Comfortable with discovery work: prototype, test, iterate, and validate before scaling Adapts quickly as requirements and technical approaches evolve Owns delivery end-to-end, driving work through production and refinement Communicates openly, contributes to design discussions, and challenges assumptions constructively Collaborates across teams and works across the stack when needed Minimum Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related technical field. Degrees in Mathematics, Statistics, Economics, or similar quantitative disciplines are also welcome 3 to 6 years of experience in Software Engineering, Data Engineering, Full Stack Engineering, or related fields Financial services industry experience is a plus but not required Relevant Professional or Industry certifications a plus Knowledge, Skills & Abilities Required Ideal candidate will have knowledge and experience in one or more of the following areas which are essential to be effective and successful in this role: Core Requirements Strong software engineering fundamentals with production experience in TypeScript/Node.js and/or Python/Flask, (bonus: AI/chat/workflow UX, streaming responses) Strong software development experience on DevOps, Container (Docker) technologies, and GitHub. Strong IaC experience ( CloudFormation/Pulumi), Terraform background nice to have. Hands-on experience shipping AI applications into production Experience using LLM coding tool like Claude Code, OpenAI Codex or GitHub Copilot Experience designing and developing MCP and applications using agentic workflows Strong SQL and experience with Postgres/Aurora or similar Experience integrating OAuth2/OIDC for secure authentication/authorization (SSO, token flows, RBAC) AWS experience (infrastructure, observability, CI/CD) Nice to Have Experience in regulated environments: auditability, PII handling, data entitlements Exposure to data governance and security practices in cloud environments Compensation Pay Range: $160,000 - $180,000 This position is a hybrid opportunity based in our Chicago office.
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.