Role Overview
A leading financial services organization is building enterprise-wide AI capabilities to improve how software is designed, developed, tested, deployed, and operated. The organization is looking for a hands-on engineer who can turn GenAI ideas and coding-agent concepts into secure, scalable, production-ready solutions.
Key Responsibilities
Design and build AI-powered agents and reusable engineering capabilities for software delivery workflows such as code generation, code review, testing, documentation, and developer productivity.
Turn prototypes into robust, scalable solutions that can be adopted by multiple engineering teams.
Integrate agentic capabilities into existing developer tools, platforms, and workflows.
Lead technical decisions across APIs, cloud platforms, AI workflows, orchestration, security, reliability, and cost.
Coach engineers on the effective and responsible use of GenAI and coding agents.
Measure the value and impact of AI-enabled capabilities across the software development lifecycle.
Required Experience
5+ years of experience in software engineering, DevOps, ML engineering, data science, or a related technical role.
Strong end-to-end software engineering experience, from architecture and development to testing, deployment, and production operations.
Hands-on experience with cloud platforms, DevOps practices, and Infrastructure as Code such as Terraform or Bicep.
Strong coding ability and a polyglot engineering mindset, with comfort working across languages, tools, and systems.
Practical experience with GenAI, coding agents, or agentic development tools through production work, prototypes, or serious side projects.
Good understanding of security, observability, compliance, reliability, and production readiness.
Experience working in Agile teams and collaborating with engineering, platform, product, and business stakeholders.
Candidate Profile
The ideal candidate is a strong builder with solid engineering fundamentals, curiosity for GenAI, and the drive to deliver real impact. You are comfortable with ambiguity, make pragmatic technical decisions, communicate clearly, and know how to move from idea to working software quickly and responsibly.
Why This Role
This is a high-impact opportunity to help shape the future of software engineering in a large enterprise environment, with freedom to experiment, build reusable capabilities, and influence how many engineering teams work with AI.
