AI Solutions Engineer

As an AI Solutions Engineer, you will be one of Sleek's most senior individual contributors, responsible for turning AI and automation opportunities into deployed, measurable business capabilities across our Accounting, Corporate Secretarial, Compliance, Sales, Marketing, HR, and Finance teams.

This is a highly hands-on role. You will take ambiguous, manual business processes from discovery and specification through coding, deployment, monitoring, support, and eventual handover to the business team.

You will work closely with non-technical subject-matter experts and senior leadership to identify high-value opportunities, build practical AI solutions, and prove that they deliver measurable business value.

The role requires someone who is equally comfortable writing production code, talking to a business stakeholder, challenging assumptions, and demonstrating why an automation is worth building.

You will also take ownership of existing automations and be expected to independently diagnose and resolve technical issues rather than relying on external technical support.

Key Outcomes in the First 6–12 Months

Outcome 1: Deliver Production AI Automations

Lead and deliver at least 3 end-to-end business automations within the first 6 months, taking each initiative from identifying the problem through discovery, specification, development, deployment, and production support.

Build against real business systems and data, including LLM APIs and SDKs, databases and warehouses, accounting APIs, Slack, document-generation workflows, and scheduled jobs.

Take ownership of stabilizing and improving existing automations where required, ensuring they are reliable, maintainable, and supported by Sleek-owned infrastructure.

Outcome 2: Generate Measurable Business Value

Target SGD $100,000+ in annualized value across 12 months, setting clear baselines and ROI metrics before building.

Measure success holistically through cost savings, capacity released, faster turnarounds, error reduction, or revenue enablement.

Track usage, costs, and adoption from day one, regularly auditing the portfolio to scale winning solutions or stop low-impact builds.

Outcome 3: Build and Hand Over Sustainable Solutions

Design low-code/config-driven interfaces that allow non-technical teams to safely operate and update daily workflows.

Provide documentation, safeguards, and power-user training for daily operations, keeping core code and infrastructure maintained under technical scope.

Build on Sleek-owned credentials with documented fallbacks, clear rollback procedures, and no reliance on personal accounts or single-point failures.

Outcome 4: Become a Trusted AI Partner Across the Business

Build strong relationships with stakeholders across Accounting, Corporate Secretarial, Compliance, Sales, Marketing, HR, and Finance across Sleek's four markets.

Independently conduct discovery with subject-matter experts, turn ambiguous requirements into practical specifications, and challenge assumptions using actual business volumes and data.

Identify opportunities proactively rather than waiting for fully defined projects, and communicate technical concepts and solutions clearly to non-technical colleagues and senior leadership.

Must-Have Experience

1. Production Software Engineering: 10+ years of professional technology/industry experience, including at least 4+ years of hands-on software development/coding experience. Proven experience independently building, deploying, monitoring, debugging, and supporting production software.
2. Python: Strong hands-on Python development experience is essential, with the ability to independently diagnose and resolve technical issues in production.
3. Production AI/LLM Systems: Proven experience building and deploying LLM-based systems into production for real users. This must go beyond prompt experimentation or using AI chat tools.
4. Agentic Development Tools: Hands-on and current experience using agentic coding tools such as Claude Code, Cursor, Replit, Codex, or similar tools. These should be tools the candidate actively uses rather than tools they are planning to learn.
5. AI Automation: Demonstrable experience building AI-powered automations, agents, workflows, or applications that solve real business problems.
6. Data & Systems: Comfortable working with SQL, data warehouses, third-party APIs, file and document formats, and integrations between different business systems.
7. End-to-End Ownership: Proven experience building a system or significant application from scratch and taking responsibility for it through production, rather than only contributing to an existing codebase.
8. Enablement: Demonstrable experience taking a non-technical colleague or business team from little or no development experience to independently maintaining or extending a tool.
9. Business Partnership: Experience working directly with non-technical stakeholders to understand problems, gather requirements, define solutions, and manage expectations.
10. Commercial Acumen: Able to establish a business baseline, develop an ROI case, and measure whether an automation has delivered genuine business value.
11. Startup Environment: Experience working in a startup, scale-up, or smaller team environment where engineers are expected to operate independently, move quickly, and take broad ownership.

Must-Have Attributes

Ownership & Accountability: Takes full responsibility for outcomes and sees problems through to resolution. Comfortable owning a system from idea to production rather than waiting for someone else to define the next step.

Initiative & Bias for Action: A proactive self-starter who actively looks for problems worth solving and prefers to ship, learn, and iterate rather than over-engineer.

Strong Communication: Personable and confident when working with both technical and non-technical stakeholders. Able to extract requirements from busy subject-matter experts and communicate technical concepts in plain language.

Commercial Mindset: Thinks beyond whether something can be built and asks whether it should be built. Comfortable defending an ROI case and stopping projects when the expected value is not materializing.

Curiosity & AI Enthusiasm: A genuine self-learner who actively experiments with new AI technologies and applies them to practical problems.

Structured Thinking: Able to take ambiguous problems, break them down into manageable components, establish priorities, and make pragmatic decisions.

Humility: Open to feedback, willing to acknowledge knowledge gaps, and comfortable learning from subject-matter experts across the business.

Resilience: Comfortable troubleshooting problems independently and working through technical or business obstacles without becoming blocked.

Nice-to-Have Experience

• Experience working in a regulated, multi-jurisdiction, or professional-services environment.
• Experience in accounting, bookkeeping, corporate secretarial, compliance, or fintech operations.
• Experience working with accounting platforms or APIs such as Xero.
• Experience with BigQuery or other cloud data warehouses.
• Experience building integrations with Slack or similar collaboration platforms.
• Experience with document-generation and document-processing workflows.
• Experience building AI agents, tool-calling systems, or multi-step AI workflows.
• Experience working with evaluation frameworks, golden sets, and production LLM monitoring.

Behavioral Fit Attributes

Ownership: Shows reliability and helps build trust within the team. Sleek moves fast and needs to know that everyone will see things through to completion and proactively help to get things back on track when challenges arise.

Humility: Allows for open-mindedness to feedback and a willingness to learn from others, fostering collaboration and a positive work environment.

Structured Thinking: Ensures solutions are pragmatic and balance the needs of the organization, team, and customers.

Attention to Detail: Ensures AI systems and automations work reliably with real business data, identifying gaps, edge cases, errors, and failure modes before they create problems for users.

Excellent Listener and Clear Communicator: Extracts what stakeholders actually need and communicates solutions clearly to both technical and non-technical audiences.

Initiative: Actively identifies opportunities rather than waiting for fully defined projects, comfortable approaching business teams, understanding their problems, and proposing practical solutions.