AI-Directed Software Engineer

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* Job Summary:

** The AI-Directed Software Engineer designs and delivers software across the full Cloud Nine stack — backend, frontend, native clients, and the infrastructure that runs them — by directing AI systems to do the bulk of the implementation work. You'll move ideas from concept to demo to production at high speed, decomposing problems into AI-executable tasks, steering and refining AI output, and owning the quality, performance, and customer impact of the result.
This is a full-stack role with a Dev Ops component. You won't be specializing in one layer. You'll own features end-to-end — from the database schema, through the Java services, through the Angular or React UI, and out through the Kubernetes deployment that ships them.
Operating in an AI-first environment, you'll push the organization from AI-assisted toward AI-delegated software delivery.
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* Job Description:

**** Our Stack
** You don't need to know all of this on day one, but you'll work across it:•
** Backend:
** Java, Maven, Jersey (JAX-RS), Jackson, Log4j, Tomcat•
** Frontend (Angular):
** Angular + Type Script , Prime

NG, Prime Flex, Transloco, Day Pilot•
** Frontend (React):
** React, Vite, Type Script, Tailwind

CSS •
** Data:
** Postgre

SQL (runtime + analytics instances), direct SQL•
** Messaging:
** Apache Active

MQ•
** Native client:
** C# / .NET Framework (Windows Zero Client), WiX / MSI installers•
** Infra & Dev Ops:
** Docker, Kubernetes, AWS (Cloud Formation, EFS, S3), Helm/Kustomize, multi-tenant cloud architecture•
** Analytics & tooling:
** Python ETL pipelines, Swagger / OpenAPIMulti-module monorepo:
Web Services (backend)
· Web Apps (Angular)
· React Web Apps  (Vite/React)
· Native Clients (C#)
· Packages (Docker/K8s).
** What You'll Own*
* • End-to-end delivery of features from concept → demo → production, across
** backend, frontend, and deployment*
* • Directing AI tools to generate code, APIs, UI, SQL, infra config, and workflows
• Decomposing product requirements into AI-executable tasks
• Validation, testing, and hardening of AI-generated output
• Kubernetes/Docker configuration and deployment of the services you build
• Throughput and cycle time across your assigned work streams
• Continuous improvement of AI-driven development patterns, prompts, and tooling
** How AI Changes This Role
** AI is your primary implementation engine. You're not expected to hand-write every line of code across every layer of this stack — you're expected to direct AI to produce it. You'll use AI to generate Java services, Angular components, React UIs, SQL, Dockerfiles, and K8s manifests alike.

Every AI-generated output is a
** starting point, not a finished product.
** You own correctness, edge cases, security, and production readiness. The breadth of this stack is exactly why AI-directed development matters here: no single engineer can be a deep expert in Java, Angular, React, C#, Postgre

SQL,
* and* Kubernetes — but one engineer directing AI across all of them can.
** What We're Looking For*
* • Strong software engineering fundamentals (APIs, distributed systems, debugging, data flows)•
** Full-stack breadth** — comfortable moving between backend services, UI, and deployment config in the same day
• Working familiarity with
** containers and Kubernetes** (or willingness to ramp fast); can debug a failing pod, read a manifest, and ship a Helm change
• Demonstrated experience using AI coding tools (Claude Code, Cursor, Copilot, or similar) to ship real work
• Sharp eye for reviewing AI output — especially subtle correctness, security, or deployment issues
• Comfort in fast, ambiguous, rapidly changing environments
• Bias toward shipping working software over perfect design
• Systems thinking — understanding how components interact at scale
• Willingness to challenge both human
* and* AI-generated assumptions
• Strong written communication — prompting is writing
** Nice to have:
** Experience with Java/Jersey, Angular or React, Postgre

SQL, AWS, or retail/POS domain.
** What Success Looks Like (First 90 Days)*
* • Ship multiple features from concept to demo-ready in ≤5 days each, touching backend, frontend,
* and* deployment where required
• Demonstrate effective…