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kAIgentic
kAIgentic
11 – 50 Employees
Artificial IntelligenceEnterpriseSaaS
kAIgentic is a Singapore-headquartered enterprise AI SaaS company helping complex, knowledge-intensive organizations turn tacit operational knowledge into governed AI agents. Its platform combines agent configuration, diagnostic analysis of people, systems, and processes, and a runtime environment for deployment with human oversight, telemetry, and ongoing refinement. With roots in Japan and enterprise financial-services collaboration, kAIgentic focuses on assurance, compliance, and practical AI modernization for regulated businesses without requiring a rip-and-replace approach.
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Senior AI Research Software Engineer – kAIgentic (Hybrid, India)

Lead the development of governed knowledge graphs, learning systems, and production AI pipelines at kAIgentic. Build reliable, evidence-grounded solutions for regulated enterprise operations.

INIndiaHybridFull-timeSeniorEnglish RequiredAI Research ScientistMachine Learning Engineer
PythonPyTorch

Description

  • Lead the full design and implementation of a knowledge-graph schema covering hierarchy, provenance, versioning, and extensibility.
  • Develop grounded-extraction pipelines that connect every claim to source evidence and an epistemic status.
  • Create and refine multi-context inference harnesses for memory management, budget control, and large-scale compaction.
  • Build knowledge-distillation workflows that bring external data into the internal ontology.
  • Develop consolidation frameworks that unify documents, interviews, and event logs while resolving conflicts.
  • Create and refine model-adaptation workflows using SFT, DPO, and RFT.
  • Develop learning-loop infrastructure that captures feedback, supports active learning, and updates the ontology continuously.
  • Build reinforcement-learning environments and curricula with reward signals and evaluation measures for safe operation.
  • Develop production retrieval-generation systems within defined quality, latency, and cost targets.
  • Create evaluation frameworks using blind rubrics and LLM-as-judge validation to assess grounding and hallucination.

Requirements

  • Demonstrated success taking AI research systems from initial prototype through production in regulated environments.
  • Work with an AI-native approach and high execution velocity.
  • Advanced Python and PyTorch expertise, including large-scale fine-tuning with SFT, DPO, and RFT.
  • Expertise in graph databases and ontology engineering, including schema architecture, version control, and provenance.
  • Practical experience building extraction systems that associate claims with source evidence and epistemic status.
  • Hands-on experience with reinforcement-learning environments, curriculum development, and reward modeling for autonomous systems.
  • Strong command of retrieval-augmented generation, latency reduction, and cost-efficient scaling.
  • Ability to conduct rigorous applied research through hypothesis design, ablation testing, and statistical validation.
  • Sound judgment when choosing between model adaptation and context engineering, with strong cross-functional communication.
  • PhD in Artificial Intelligence, Computer Science, or a related discipline.
  • At least four years of relevant industry research experience.

Benefits

  • Collaborate globally with colleagues across Singapore, India, Japan, Europe, and the United States.
  • Learn and develop alongside experienced leaders from major enterprises.
  • Take ownership of meaningful work from the first day.
  • Work in an environment that values psychological safety, candid debate, and disciplined experimentation.
  • Combine startup speed with work on enterprise-scale infrastructure.
  • Help influence the product, company culture, and customer results.
  • Address mission-critical challenges in regulated enterprise environments.

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