Software Development Engineer, II

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.

As a Software Development Engineer II, you will own significant components of kAIgentic's orchestration platform, the layer that runs stateful, long-running AI workflows for the enterprise. You will design and build the systems that keep these workflows durable, observable, and recoverable with enterprise-grade reliability under real production load.

• Design and build durable workflow systems on Temporal for multi-step, long-running processes.

• Build the orchestration layer for LangGraph-based coordination across models and tools.

• Develop self-correction loops that validate LLM outputs and trigger re-prompting on schema failures.

• Create comprehensive observability pipelines using Langfuse and Arize Phoenix.

• Implement interrupt-and-resume patterns for human-in-the-loop workflows, and own reliability and failure handling for critical workflow components.

• Drive AI-native development practices, and bring engineering rigor to code reviews and design discussions.

• Experience building backend or infrastructure systems

• AI-native velocity as a default mode of working (mandatory)

• Strong proficiency in Go and Python

• Hands-on experience with the following:

  • Durable execution engines (Temporal, Cadence, or similar)

  • LLM orchestration and self-correcting AI systems

  • Distributed systems fundamentals

  • Observability and tracing systems

  • gRPC and service mesh architectures, and state management in distributed environments

• Demonstrated ownership of complex technical projects, delivered end to end

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.