Application Developer III

Old National Bank•Saint Paul, MN

About The Position

Old National Bank has been serving clients and communities since 1834. With over $70 billion in total assets, we are a regional powerhouse deeply rooted in the communities we serve. As a trusted partner, we thrive on helping our clients achieve their goals and dreams, and we are committed to social responsibility and investing in our communities through volunteering and charitable giving. We continually seek highly motivated and talented individuals as our people are critical to our success. In return, we offer competitive compensation with our salary and incentive program, in addition to medical, dental, and vision insurance. 401K, continuing education opportunities and an employee assistance program are also included in our benefit suite. Old National also offers a variety of Impact Network Groups led by team members who are passionate about driving engagement, creating awareness of diverse backgrounds and experiences, and building inclusion across the organization. We offer a unique opportunity to join a growing, community and client-focused company that is firmly rooted in its core values. The Application Developer III designs and governs autonomous software delivery systems that convert intent into compliant, production‑grade outcomes. This role leads development, architecture, and operation of agentic workflows—integrating LLMs, services, code generation, and guardrails—to deliver secure, reliable capabilities across Old National Bank’s Product Engineering organization.While the role optimizes for outcomes over code, strong engineering fundamentals and the ability to write high‑quality software remain essential for shaping, supervising, and controlling autonomous systems. The salary range for this position is $98,400 - $199,000 per year plus bonus. The base salary indicated for this position reflects the compensation range applicable to all levels of the role across the United States. Actual salary offers within this range may vary based on a number of factors, including the specific responsibilities of the position, the candidate’s relevant skills and professional experience, educational qualifications, and geographic location.

Requirements

6-8 years of professional software engineering experience with ownership of complex, production systems.
Strong coding proficiency in Golang, Python, and TypeScript, including API design, integration patterns, and cloud‑native development.
Experience with AWS, GitOps CI/CD, serverless architectures, and Terraform.
Hands‑on experience integrating LLM platforms (AWS Bedrock, Anthropic), embeddings/vector stores, and orchestration frameworks (AWS Bedrock AgentCore, or similar).
Familiarity with AI evaluation/observability, guardrails, policy‑as‑code, and designing secure, compliant systems in regulated environments.

Responsibilities

Own intent‑to‑outcome delivery: convert business intent/specifications into shipped, compliant features using agentic and autonomous workflows.
Write and review high‑quality code: write in Golang, Python, and TypeScript when establishing patterns, building secure components, integrating services, or ensuring agent‑produced code meets standards.
Testing & validation: ensure autonomous and human-written code is validated through automated testing frameworks, and continuous verification to maintain safety and correctness.
Optimize for outcomes, not code volume: improve cycle time, reliability/SLOs, quality, and delivery economics; deploy human coding effort where it provides leverage or safety.
Risk & readiness: identify ambiguity, dependencies, and operational risk early; harden prototypes into resilient production systems.
Architect and orchestrate AI systems: use LLMs, RAG pipelines, program synthesis, CI/CD generation, and runtime automation.
Cloud foundations: design and operate AWS cloud‑native/serverless systems using GitOps CI/CD workflows and Terraform.
Cross‑functional leadership: collaborate with product, security, risk, and compliance to define intents, acceptance criteria, and controls.
Governance & safety: implement responsible‑AI controls, evaluation frameworks, guardrails, and human‑in‑the‑loop reviews to ensure compliant outcomes in a regulated environment.
Mentorship & review: mentor engineers in agentic workflows, AI‑evaluations, software design, and coding best practices; lead design and code reviews.