kAIgentic - Principal Engineer, AI Infrastructure & Platform
Requirements
• Proven expertise in backend, platform, or infrastructure engineering with deep ownership of distributed systems at scale, including platform architecture decisions that held at 10x to 100x scale and recognized technical authority through publications, patents, open-source leadership, or equivalent industry impact. • Expert-level mastery of Go and Python including runtime semantics, concurrency models, and production behavior under load. AI-native velocity as a default mode of working (mandatory). • Built and operated durable execution systems in production, including Temporal or Cadence internals (scheduler design, replay semantics), distributed consensus, state-machine replication, and long-running workflow systems with guaranteed execution and audit integrity. • Architecture experience for building the control plane of a high-concurrency, low-latency enterprise platform, including multi-agent orchestration across state partitioning and coordination protocols, cross-language service architecture (gRPC, Protobuf, service mesh), and observability at multi-tenant scale. • Experience taking research prototypes into safe platform primitives the rest of engineering can build on, with strong instincts for the developer experience and AI-facing surfaces (streaming, human-in-the-loop interactions, error states, SDK ergonomics) that sit on top of the platform.
Responsibilities
• 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.
Benefits
• 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 • 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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