Codex AI Engineer: Enterprise Workflow Architect in Sydney

About BJAK

The original mission of BJAK is we believe people deserve smarter ways to plan, save and grow their money. This is the origin of our name.

Started in 2019, we built the first mobile‑first insurance platform, enabling insurance to be accessible online by millions in the region.

Today, its the leading insurance platform in Southeast Asia.

Today, we are expanding ways to help people in the region — this includes spending, saving, investing, exchanging, travelling, and more.

Our mission is help people get more from their money every day.

We have teams working around the world, with over 20 nationalities from our offices and remotely, who truly enjoys their work.

We are looking for the most talented and driven people we can find.

We are looking for people who work for their passion, not counting hours.

Who loves building great next‑generation products, not status quo.

Who cares about redefining how everyone around us can get the best financial applications, not for an exclusive few.

If you're this person, we'd love to talk to you.

The Role

We are looking for applied AI engineers to build AI‑native systems for BJAK's AI Neobank app.

This is not a research‑only role.

We need builders who can use AI to automate real workflows, improve products, reduce manual work and make financial services easier for users and teams.

• What You Will Build
• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.
• Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.
• Create AI‑assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence.
• Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production.
• Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust.
• Turn manual processes into reliable AI‑enabled systems that can scale.
• What We Look For
• Hands‑on engineering ability, not just AI strategy or management experience.
• Experience building AI agents, LLM apps, RAG systems, automation workflows, copilots or AI‑enabled tools.
• Strong coding ability in Python, Type Script, Java Script or similar practical stack.
• Good judgement on what should be automated and what should not.
• Able to ship working systems, test quality and improve reliability over time.
• Fintech, banking, support automation, risk, KYC, fraud, CRM or operations automation experience is a strong plus.
• This Role Is Not For
• People who only want research projects with no production ownership.
• Candidates who treat AI as demos instead of working systems.
• Engineers who do not care about evaluation, reliability or user impact.
• People who overclaim AI impact without evidence.
• Builders who cannot work with product, ops and business teams.
• The Bar

We are looking for engineers with real technology career highlights.

A strong highlight is not just working at a famous company.

A strong highlight means you personally helped build, ship or scale a serious product, platform or system.

• Location
• This role is remote, but candidates must be based in

Australia . We are hiring specifically for this market, so applicants should already be based in

Australia .

Language

English is our main working language across global teams. Strong English communication is required.

• Interview Process
• Online assessment or practical task.
• Technical interview.
• CEO / final round.

For strong candidates, we aim to complete the process and make an offer within 1 week from the start of the interview process.

Candidates who complete assessments quickly will be prioritized.

Key responsibilities

• Design, build and ship complex AI platforms, services and products that solve meaningful business problems at enterprise scale.
• Engineer robust LLM, retrieval‑augmented generation, agentic and orchestration solutions, with reliability, evaluation, observability and governance built in from the start.
• Take AI capabilities from experimentation into production, including testing, deployment, monitoring, incident response and continuous improvement.
• Lift engineering standards across prompt and context management, model evaluation, security, privacy, compliance and Responsible AI guardrails.
• Make practical trade‑offs across model quality, latency, cost, risk and customer impact in fast‑moving delivery environments.
• Partner with product, platform, data, risk, security and business teams to scale AI safely and sustainably.
• Review designs and code, mentor engineers and establish reusable patterns that accelerate safe production delivery.
• Lead technical investigations, root‑cause analysis and durable fixes for complex AI system issues.
• Key Ingredients for Success
• Significant hands‑on AI engineering experience gained in a complex corporate, technology or enterprise environment.
• A strong record of delivering AI, machine learning or LLM‑enabled systems that have been deployed, governed, monitored and operated in production.
• Solid software engineering foundations across Python, APIs, cloud services, distributed systems, CI/CD, automated testing and modern delivery practices.
• Deep practical experience with LLMs, RAG patterns, embeddings, agents, evaluation frameworks, orchestration, model lifecycle management and monitoring.
• Experience embedding safety, privacy, compliance, explainability, reliability and operational risk controls into AI solutions.
• The ability to shape technical direction, raise engineering standards and bring stakeholders with you through ambiguity and change.
• Clear communication skills across engineering, product, delivery, risk and senior stakeholder audiences.
• What Success will look like
• AI solutions progress beyond prototypes to become trusted, secure and production‑ready enterprise capabilities.
• Engineering patterns are clear, reusable and adopted across teams.
• AI risks are identified and designed out early through strong architecture, governance and operating discipline.
• Systems are observable, resilient and continuously improved using real usage, feedback and performance data.
• Engineers around you grow through practical mentoring, thoughtful design review and strong technical examples.

Does this sound like you?

We’re all about creating a supportive and inclusive community.

We welcome everyone – no matter your age, gender, background, or abilities.

We also provide added support to welcome our veterans, Indigenous Australians, and neurodiverse community.

Work rights and background checks

To be eligible for a position with us, applicants will need to have valid work rights for Australia and be willing to undergo a comprehensive background checking process, including probity and police checks.

Equal opportunity

Cognition is an equal opportunity employer.

We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status or any other protected characteristic under applicable law.

We are committed to providing reasonable accommodations for candidates with disabilities throughout the recruitment process – please let us know if you need any.

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