Artificial Intelligence Engineer

About CBTW

We are a global tech solutions company that believes Collaboration Betters the World.

Leveraging strategy, technology, and design, we partner with organizations worldwide to offer comprehensive solutions from idea conception to product realization. We work with people around the globe to advise, build, run, and support the creation of products with purpose.

The Opportunity: Build and Ship AI-Enabled Software

CBTW is evolving from a traditional digital service provider into an “AI-First Engineering Partner.” We are looking for a strong software engineer who can design, build, test, deploy, and operate production systems that incorporate AI capabilities. The majority of the role is software engineering, systems integration, cloud development, and production delivery.

As CBTW becomes an AI-first engineering company, we would rather hire a strong software engineer with AI experience than an “AI engineer” with weak software engineering fundamentals. Engineering fundamentals come first; AI is how we build.

To be clear about scope: this role builds with AI, it does not build its own foundation models. We are not looking for someone to train or fine-tune large models from scratch — we want an engineer who integrates and orchestrates existing AI models, agents, and platforms into reliable software.

Note: This role is not expected to research, train, or build foundation models. The focus is on engineering with existing AI models, agents, and platforms.

Key Responsibilities

1. Design and Build Production Systems with AI

• Design and build reliable distributed systems, APIs, workflows, and integrations that incorporate AI capabilities while meeting production requirements for security, scalability, observability, and resilience.
• Build AI-enabled applications using the most appropriate platforms and frameworks, including agent platforms such as UnifyApps where appropriate.
• Design, code, and ship AI-enabled features and agent applications to production — moving well beyond proofs of concept and demos.
• Implement concrete client use cases end to end — for example, integrating an application with AWS cloud services and building the supporting agent workflows.

2. Integration, Deployment, and Hands-On Delivery

• Work directly with project teams and pods to develop, integrate, test, and deploy AI pipelines and automation into existing systems.
• Own the engineering lifecycle of your work: development, CI/CD, deployment, and operational reliability.
• Apply cloud and (where relevant) edge development practices to take solutions from local prototype to a running, supported system.

3. Quality, Testing, and Engineering Practices

• Apply test-driven development and modern engineering practices to keep AI-enabled features reliable and maintainable.
• Use AI coding tools efficiently and at an advanced level in your own workflow — beyond simple chat — to accelerate development, debugging, and refactoring.
• Contribute reusable components and patterns that strengthen CBTW's standard engineering practices.

4. Risk, Security, and Governance

• Build with security, risk, and governance in mind, avoiding unsafe or non-compliant solutions, especially given client exposure in regulated sectors.
• Ensure AI integrations respect data protection requirements and CBTW's “Private AI First” approach (e.g., minimizing data leakage).

5. Technical Client Collaboration

• Collaborate with client engineering teams at a technical, integration level — coordinating delivery, not acting as a sales evangelist.
• Translate client requirements into working integrations and communicate clearly with technical stakeholders.

Qualifications

Must-Haves

• Software Engineering Experience: 5–8+ years of professional software development experience at an intermediate level, with a proven track record of shipping and supporting production systems (not prototype/POC-only).
• Python: Strong, hands-on Python proficiency (mandatory).
• Engineering Fundamentals: Solid understanding of SDLC, CI/CD, DevOps, automated testing, and test-driven development.
• Modern AI Tooling in Practice: Advanced, efficient use of AI engineering tools such as Cursor, Claude Code, and GitHub Copilot — using agentic coding assistants to build, debug, and refactor, not just simple chat.
• AI Application Development: Experience integrating LLM APIs and building agent or RAG-based applications and automation into real software.
• Modern AI Stack: Familiarity with the modern AI stack — modern AI integration patterns, protocols, orchestration frameworks, and context-management approaches, vector databases, and RAG architecture patterns.
• Cloud: Working experience with a major cloud platform (AWS preferred), with openness to edge development.
• Rapid Learning: Demonstrated ability to learn new tools and platforms (e.g., UnifyApps) quickly as the AI landscape changes.

Nice-to-Haves

• Experience building on agent platforms (e.g., UnifyApps).
• Background in banking or financial systems, valued due to client exposure.
• Exposure to risk, security, and governance practices for software delivery.
• Experience with legacy modernization (e.g., refactoring, .NET migrations, monolith-to-microservices) accelerated by AI tooling.

We offer

• Competitive Salary.
• Language courses.
• Sodexo food card.
• Health and life insurance.
• Being part of a global team.
• Continuing education opportunities.
• Virtual company events each month.
• Multicultural and inclusive work environment.
• Career development and professional growth opportunities.
• Paid Time Off (vacation, sick leave, maternity and paternity leave, COL holidays).

CBTW is committed to building inclusive and diverse teams, and a workplace that is free from discrimination and harassment, because that’s how we create better products and services, make better decisions, and better serve the communities we’re a part of, we are proud to be an equal opportunity workplace.

Collaboration Betters The World – let’s do something great together!

Join our talented team!