Software Engineer, Applied AI

POSITION: Software Engineer, Applied AI

DIRECT REPORT: Sr. Director, AI and Architecture

COMPENSATION: Pursuant to state regulations, the salary range is $120,800-$133,300 plus bonus potential. ​Eligible to participate in the company benefits plan. We offer health, vision, dental, and pet insurance. We offer a 401(k) retirement plan, student loan assistance, licensing and continuing education reimbursement, parental leave, and housing allowances or gifts.

SUMMARY

The Software Engineer, Applied AI is responsible for designing, building, and supporting production software and AI solutions that solve business problems across Cardinal. Working across the full software development lifecycle, this role owns solutions end-to-end, including web applications, APIs, integrations, and AI agents. The engineer works AI-natively, using agentic development tools such as Claude Code and GitHub Copilot as everyday collaborators, while bringing the engineering mindset and computer science fundamentals needed to direct, review, and verify AI-generated work so that what ships is secure, tested, and maintainable. Operating with a high degree of independence, this role moves quickly from prototype to production, partners with senior engineers on architecture, and helps raise the technical bar across the team.

RESPONSIBILITIES (Including but not limited to)

• Translate business requirements into well-designed technical solutions, including web applications, APIs, integrations, automated workflows, and AI agents, and own their delivery end-to-end, from rapid prototypes that validate ideas with stakeholders to hardened production releases.

• Build backend services and RESTful APIs using Python and FastAPI, and front-end applications using TypeScript and Angular.

• Use agentic development tools (e.g., Claude Code, GitHub Copilot) as a core part of the daily workflow, from planning and specification through implementation, testing, and documentation, including delegating well-scoped tasks to coding agents and rigorously reviewing the results.

• Build and maintain the team's shared AI development assets, such as agent instruction files, reusable skills and commands, and Model Context Protocol (MCP) servers, to make AI-assisted development faster and more consistent.

• Design, build, and operate AI agents and LLM-powered features using frameworks such as Google Agent Development Kit (ADK) or LangGraph, applying tool calling, retrieval-augmented generation (RAG), structured outputs, and multi-agent patterns where appropriate.

• Bring the same rigor to AI features that the team applies to conventional software: build evaluation datasets and automated evals, instrument tracing and monitoring, and track quality, cost, and latency in production.

• Write and maintain automated tests (unit, integration, end-to-end) and contribute to CI/CD pipelines in GitHub Actions, including automated quality gates and AI-assisted code review.

• Deploy and operate solutions on Google Cloud Platform (GCP), including Cloud Run, Cloud SQL, BigQuery, and Vertex AI, using containers and infrastructure-as-code where appropriate, and participate in production support, including troubleshooting, root-cause analysis, and reliability improvements.

• Design data models and build integrations with internal and third-party systems using APIs, webhooks, and event-driven messaging, ensuring reliable data flows.

• Apply secure-by-design practices, including authentication and authorization, secrets management, least-privilege access for agents and their tools, protection of resident and team member data, and mitigation of AI-specific risks such as prompt injection.

• Contribute to architecture and technical design discussions alongside senior engineers, documenting decisions and trade-offs.

• Perform thorough code reviews of both human- and AI-authored code, contribute to team coding standards, and help mentor associate team members.

• Collaborate directly with business stakeholders and cross-functional partners, including data engineering, to clarify requirements, demo working software early, and communicate technical decisions in accessible terms.

• Participate in sprint ceremonies, provide estimates, and surface technical risks and dependencies early.

• Evaluate new AI models, tools, and frameworks through small proofs of concept, and assess platform, framework, and model updates (including model deprecations) for impact on existing solutions.

• Support Cardinal OKRs as needed.

• Participate in Cardinal U training as required.

QUALIFICATIONS

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or an equivalent combination of education and experience.

• Three (3) to five (5) years of professional software engineering experience, including designing, building, and supporting applications in production.

• Strong computer science fundamentals (data structures, algorithms, system design) and software design skills (API design, data modeling, design patterns), with the judgment to recognize when AI-generated code falls short.

• Proficiency in Python and TypeScript, with experience building RESTful APIs (FastAPI preferred) and front-end applications with a modern framework (Angular preferred).

• Demonstrated daily use of agentic AI development tools (e.g., Claude Code, GitHub Copilot, Cursor), including the ability to plan, direct, and verify AI-generated work.

• Experience building and shipping LLM-powered applications or AI agents, including tool calling, RAG, and prompt and context engineering, using Google ADK, LangGraph, or similar frameworks.

• Experience with automated testing, Git-based workflows, code review, and CI/CD pipelines (GitHub Actions preferred).

• Hands-on experience deploying and operating applications on a major cloud platform (GCP preferred), including containers (Docker) and serverless services.

• Strong SQL skills and experience with relational databases (PostgreSQL preferred); experience with BigQuery or another analytical data platform is a plus.

• Working knowledge of application security, including OAuth 2.0/OpenID Connect, secrets management, the OWASP Top 10, and LLM-specific risks such as prompt injection.

• Familiarity with MCP, LLM evaluation and observability practices, and the capability, cost, and latency trade-offs across major model families (Gemini, Claude, OpenAI) is preferred.

• Experience with infrastructure-as-code (e.g., Terraform), event-driven architectures, C#/.NET, Azure, or property management platforms such as Entrata is a plus.

• Ability to work independently through ambiguity, break problems into deliverable increments, and know when to pull in senior team members.

• Strong communication skills, with the ability to explain technical decisions and trade-offs to both technical and non-technical stakeholders.

• A continuous-learning mindset and genuine curiosity about the rapidly evolving AI landscape.

• Champion the Cardinal Culture and Cardinal Core Values every day.

WORK ENVIRONMENT

The work environment characteristics described here are representative of those a Team Member encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Incumbents work in an office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.

PHYSICAL DEMANDS

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the Team Member is regularly required to use hands to finger, type, handle, or feel and talk or hear. The Team Member is frequently required to stand; walk; reach with hands and arms, and stoop, or squat. The Team Member is often required to sit. The Team Member must be able to push, pull, lift, carry, or maneuver office products and supplies of up to twenty (20) pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus.

The above job description is not intended to be an all-inclusive list of duties and standards of the position. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their Team Leader.