AI-Directed Software Engineer

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 DevOps 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.

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 + TypeScript , PrimeNG, PrimeFlex, Transloco, DayPilot

• Frontend (React): React, Vite, TypeScript, TailwindCSS 

• Data: PostgreSQL (runtime + analytics instances), direct SQL

• Messaging: Apache ActiveMQ

• Native client: C# / .NET Framework (Windows ZeroClient), WiX / MSI installers

• Infra & DevOps: Docker, Kubernetes, AWS (CloudFormation, EFS, S3), Helm/Kustomize, multi-tenant cloud architecture

• Analytics & tooling: Python ETL pipelines, Swagger / OpenAPI

Multi-module monorepo: WebServices (backend) · WebApps (Angular) · ReactWebApps (Vite/React) · NativeClients (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 workstreams

• 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#, PostgreSQL, 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, PostgreSQL, 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 use of AI to produce production-quality code across the stack

• Establish repeatable, documented workflows for AI-directed development

• Measurably improve delivery speed and consistency across your workstreams

• Validate and harden AI-generated output before it reaches customers

• Help move the team from AI-assisted → AI-directed development

Bottom Line

This is a full-stack + DevOps role, and that's exactly why AI makes it possible. If you can take an idea, direct AI across Java, TypeScript, SQL, and Kubernetes, and deliver something that works in days — this is the job.

Worker Type:

Regular

Number of Openings Available:    

1