PRINCIPAL

Principal Engineer, AI Infrastructure & Platform

kAIgenticVisit website ↗·Posted 3 weeks ago

Location

KA, IN

Required Skills

PythonGoAIDevOps

About the Role

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
As Principal Engineer, AI Platform . Infrastructure, you will be a senior technical owner for the core architecture behind kAIgentic’s orchestration platform. Working closely with the CTO and engineering leadership, you will translate company-level technology strategy into durable, production-grade systems. You will make high-judgment architecture decisions across platform infrastructure, stateful execution, reliability, security, scalability, and enterprise-grade compliance.

This is a role for someone who can go deep into distributed systems and AI platform infrastructure, turn ambiguous platform problems into clear technical designs, and see those designs through to real-world deployment. You will shape how engineering teams think about durable execution, stateful AI systems, observability, auditability, and production reliability. You may also support high-trust technical conversations with banking partners, regulators, and enterprise customers where deep platform expertise is required. The work sits at the intersection of distributed systems, AI infrastructure, and enterprise compliance. You may lead a lean, embedded technical team on the highest-priority platform programs, while partnering closely with the CTO on broader platform direction.

What You'll Do

• Own the architecture and execution of core platform systems that power kAIgentic’s orchestration layer, translating company-level technology strategy into concrete designs, platform primitives, and production systems.

• Make high-judgment architecture decisions across durable execution, state management, workflow reliability, observability, availability, scalability, security, and enterprise-grade compliance

• Design and build systems for long-running, stateful AI workflows that require auditability, recoverability, deterministic behavior, and production-grade reliability.

• Solve hard platform problems across workflow semantics, model non-determinism, human-in-the-loop execution, failure recovery, and real-world operating constraints.

• Partner deeply with AI Infrastructure, DevOps/MLOps, AI Research, Product, and Security to ensure platform decisions hold across customer, banking, and regulated environments.

• Raise the engineering bar through architecture reviews, design reviews, mentoring, and hands-on technical leadership, while leading a lean embedded team on the highest-priority platform programs.

What You'll Bring

• Deep backend, platform, or infrastructure engineering experience, with a proven ability to design, build, and operate distributed systems under real production complexity.

• Strong track record of making platform architecture decisions that held under scale, ambiguity, and production pressure.

• Expert-level depth in Go and Python, including runtime behavior, concurrency models, and production performance under load.

• Deep expertise across several of these areas: durable execution engines, longrunning workflow systems, stateful orchestration, control-plane design, observability, multi-tenant platforms, service architecture, security, and compliance-driven systems.

• Experience building systems that require auditability, reliability, recoverability, operational trust, and enterprise-grade governance.

• AI-native velocity as a default mode of working, with the ability to communicate complex technical decisions clearly across engineering, product, executive, customer, and compliance audiences

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.

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