Principal Engineer - AI

kAIgentic is building the intelligence layer for the world's most ambitious enterprises. Headquartered in Singapore with teams in India and Japan, our software platform helps large organizations evolve as fast as technology itself by turning the tacit know-how locked inside their people into safe, governed, AI-powered operations.

The hardest part of enterprise transformation is not strategy. It is execution. Institutional knowledge lives in people's heads, systems are fragmented, and risk tolerance is low. kAIgentic captures how work actually happens, designs better workflows, and runs them inside an intelligence layer that is observable, auditable, and engineered for the most regulated environments on earth. The outcome is an enterprise that continuously improves.

We are backed by SMBC Group as our founding partner and customer zero, and our platform is already being proven inside one of the most complex, regulated operating environments in the world. That means real problems, real data, and real production impact from Day 1.

The role

kAIgentic is building agentic AI for enterprise banking, compressing work that once took large consulting teams years into something our platform does in a fraction of the time. That only holds up if the AI underneath is genuinely reliable, because our customers operate in high-trust, heavily regulated environments where a wrong answer carries real consequences.

This role owns exactly that. You'll take core AI systems that already work and make them production-grade: accurate, dependable, and trustworthy across a growing range of customers, processes, and regulatory contexts. You'll partner closely with the CTO, our engineering team, and the domain experts already in the company to turn strong AI into AI a bank can rely on every single time.

This is a builder and operator role at heart. The person who thrives here has spent years making a real AI product better and better, the way the best production systems keep getting improved until they simply work.

What you'll do

• Own the end-to-end quality and reliability of our core AI systems, from how well they interpret messy real-world enterprise data to how faithfully their output reflects reality.

• Define what "good" means for each part of the system and build the evaluation infrastructure to measure it continuously against ground truth. Measurement comes before optimization, always.

• Drive the hard optimization work on probabilistic systems: raising accuracy, cutting hallucination, and getting dependable behavior out of models under real-world variation and stress.

• Design the mechanisms that let the platform learn from every human correction, so the system gets sharper with every process it handles.

• Architect how our AI holds up across different process types, geographies, and regulatory regimes, working alongside our in-house domain experts.

• Push steadily toward higher automation as we scale from early customers to many, so the system handles more on its own over time.

• Own the production characteristics that matter at scale: latency, throughput, and cost.

• Define the metrics and observability that surface reliability signals for our AI services in real time.

• Represent kAIgentic in technical conversations with banking partners and regulators when reliability and compliance are on the table.

What you'll bring

• A real track record of taking a single AI product from working some of the time to working reliably at scale. You've lived the journey where an existing system gets pushed all the way to production-grade, across a growing and varied customer base.

• Architect-level command of Python and the modern AI engineering stack, including deep-learning frameworks, model serving, and data pipelines.

• Deep knowledge of LLMs, generative AI, and retrieval-augmented generation, along with the techniques that keep inference dependable under stress.

• Hands-on experience turning unstructured, heterogeneous enterprise data into clean, structured, trustworthy output.

• The instinct to build measurement first. You don't trust a change until you can show it moved the number.

• Experience building auditable, explainable, and recoverable AI in environments with real governance and compliance demands.

• Strong judgment on where to spend effort, and the ability to explain a complex technical decision clearly to engineers, product leaders, customers, and regulators.

Why join kAIgentic?

We are a global team of builders who thrive in ambiguity, care deeply about the customers we serve, and believe the intelligence layer is how enterprise work will be reshaped over the next decade. We are building the connective tissue that lets large companies operate with the speed of a startup and the trust of an institution.

We look for people who:

• Combine technical excellence with genuine customer empathy.

• Are entrepreneurial and energized by zero-to-one problems with no playbook.

• Lead with ownership, integrity, and collaboration, not titles.

• Want to help define a new category of enterprise AI, not just ship inside an existing one.

• Working here means being surrounded by peers who challenge assumptions, celebrate progress, and build with both courage and care.

Life at kAIgentic

• Intelligence layer at the core. You will be shaping the substrate that turns institutional knowledge into governed, production-grade operations. This is enterprise infrastructure with real consequences.

• Innovation at enterprise scale. Startup velocity meets the depth, scale, and stakes of mission-critical, regulated environments. Both are non-negotiable.

• Ownership from Day One. Your work directly shapes the product, the culture, and the outcomes our customers see.

• Learning and growth. You will work alongside seasoned leaders from leading enterprises who have built and scaled global businesses.

• A culture of trust. Psychological safety, transparent disagreement, and disciplined experimentation are how we operate, not slogans on a wall.

• Global collaboration. Teams across Singapore, India, Japan, Europe, and the US, working as one.

• A mission worth the effort. Building something the world has not seen before: anintelligence layer that helps enterprises continuously improve how they run.