Software and Applied AI Engineer

Salary: $100,000 – $120,000 per year

About the Role

Traffic Safe NZ is a 100% New Zealand owned and operated company that provides temporary traffic management services throughout the North Island.

We are seeking an experienced Software and Applied AI Engineer to build, enhance and support enterprise software, internal AI tools and practical agentic systems.

This hands-on individual contributor role combines full-stack development, legacy application support, AWS cloud-native engineering and AI-assisted delivery. You will independently own work from requirements through production support, collaborate with IT Operations and business stakeholders, and contribute to architecture and engineering standards.

Key Responsibilities

• Own end-to-end software delivery: Analyse requirements; design, develop, test, deploy and maintain secure, scalable applications with performance and resilience appropriate to business-critical workloads.

• Maintain and modernise existing systems: Fix defects, develop features and integrations, and incrementally improve legacy applications while new systems are developed.

• Coordinate application support: Work with IT Operations and support colleagues to triage requests, agree priorities, investigate production issues, perform root-cause analysis, coordinate fixes and releases, and maintain support documentation.

• Build full-stack solutions: Develop backend services, REST APIs, integrations and web applications using C#, .NET, JavaScript/TypeScript, Angular, SQL and NoSQL. Design databases and optimise queries.

• Manage releases and cloud delivery: Maintain builds, environment configurations, deployment automation and CI/CD pipelines using GitHub Actions, AWS CodeBuild/CodePipeline, Jenkins or similar platforms. Support AWS containerised and serverless applications and environment automation.

• Ensure quality, security and reliability: Write maintainable, documented code and automated unit, integration and functional tests. Contribute to code reviews, architecture and engineering standards. Implement DevSecOps checks, authentication, authorisation, least-privilege access and secure secrets handling. Monitor availability, logging and performance; address recurring faults and improve backup, recovery and resilience.

• Build AI engineering tools and business workflows: Develop tools supporting requirements, design, code generation, testing, documentation and delivery. Build and support LLM integrations, retrieval-augmented generation (RAG) and agentic systems that plan tasks, use tools and APIs, execute workflows and verify results.

• Direct and validate AI-assisted work: Use Claude Code, GitHub Copilot, OpenAI Codex, Cursor or comparable tools, remaining accountable for generated work. Define agent tasks, context and acceptance criteria; conduct separate reviews and obtain human sign-off at agreed decision points.

• Make AI solutions reusable and controlled: Create shared skills, prompts, agents and workflow components. Evaluate accuracy, reliability, latency and cost; implement logging, access restrictions, safeguards and fallback or human review paths. Protect confidential data and credentials, restrict agent actions and mitigate malicious instructions in retrieved content or tool responses.

• Collaborate and improve: Work with business stakeholders, engineering teams and external vendors; share knowledge and improve development workflows, automation, testing and engineering practices.

Required Skills and Experience

• Mandatory: 6+ years of full-time enterprise software development and production support experience. Internships may not count towards this minimum.

• Experience with C# and .NET Framework and/or modern .NET, such as .NET 8 or later. Experience in other stacks, including Java, Node.js or Python, will also be considered.

• Frontend development with JavaScript/TypeScript and Angular; sound knowledge of REST APIs, backend services, distributed applications, object-oriented programming, SOLID principles and design patterns.

• Hands-on SQL and NoSQL experience, such as Microsoft SQL Server and MongoDB, including complex queries, stored procedures and database performance optimisation.

• Experience with Git, collaborative development, enterprise builds and releases, CI/CD, automated deployments, and unit, integration and functional testing using modern frameworks.

• Experience maintaining legacy applications, triaging defects, troubleshooting production issues and performing root-cause analysis. Ability to coordinate with IT Operations and support teams and clearly communicate progress and resolutions.

• Hands-on AWS application development, deployment and support across relevant compute, storage, database, networking, security and monitoring services. Relevant services include EC2, Lambda, S3, RDS, API Gateway, Elastic Load Balancing, IAM, Secrets Manager and CloudWatch. Depth in services used in delivered applications matters more than coverage of every service listed.

• Familiarity with Docker, containerised architectures, microservices, scaling, deployment and image management using ECS, Fargate and ECR. Kubernetes familiarity is also relevant.

• Ability to automate engineering and operational tasks using Python, Bash or PowerShell.

• Understanding of secure coding, authentication, authorisation, application security and DevSecOps, including dependency scanning, secret scanning and CI/CD security checks.

• Regular use of coding assistants or development agents, with evidence of reviewing generated changes for behaviour, security and test coverage.

• Practical experience building AI applications, internal development tools or agentic workflows using LLM APIs connected to business data, application services and tools.

• Understanding of prompt and context engineering: clear instructions, suitable examples, relevant project knowledge and controlled tool access.

• Familiarity with harness and loop engineering: configuring agent execution environments and using tests, feedback, iteration limits and completion criteria to guide work.

• A traceable approach to AI-supported delivery, with separate implementation and review, agreed governance and human sign-off for significant decisions.

• Awareness of AI risks, including confidentiality breaches, exposed credentials, prompt injection, excessive permissions and unreliable responses. Examples of documented, reusable prompts, skills, agent configurations or automation shared with colleagues.

• Clear communication, practical problem-solving and attention to detail, with the ability to work independently across teams, explain technical issues to business users, prioritise deliverables and follow issues through to resolution.

Desirable Skills

• React, Next.js and Node.js.

• Microservices and event-driven systems using SQS, SNS, EventBridge or Step Functions.

• Infrastructure as code using Terraform, AWS CDK or CloudFormation, and delivery automation using GitHub Actions or AWS developer tools.

• AWS data integration and processing, including Glue; backup, disaster recovery and high availability.

• Observability using CloudWatch, X-Ray, OpenTelemetry or similar tools.

• Amazon Bedrock or other managed AI platforms; orchestration frameworks, RAG, embeddings, vector search and automated AI evaluation.

• Delivery through multiple AI agents, including task decomposition, coordination, validation and integration of outputs.

• Agile/Scrum delivery and support of business-critical production systems and internal enterprise platforms.

Qualifications and Personal Attributes

A degree in Computer Science, Software Engineering, Information Technology or a related discipline is preferred.

You will be practical, reliable, organised, delivery-focused and calm under pressure, with strong analytical thinking, ownership, follow-through and documentation habits. You should be comfortable balancing legacy support with new software and AI delivery, maintaining confidentiality, sharing knowledge and proactively improving processes. Curiosity about emerging AI capabilities and sound judgement about when human review is needed are essential.

Working Rights

Applicants must already hold valid New Zealand work rights. Visa sponsorship is not available.

How to Apply

Submit your CV and a brief cover letter explaining your interest in the role and how your experience meets its requirements.