---
title: 'AI Research Scientist at kAIgentic'
canonical: 'https://feeny.ai/job/ai-research-scientist-kaigentic-bengaluru-zz4vnt99x9f9'
type: 'job'
last_seen: '2026-10-17'
---

# AI Research Scientist at kAIgentic

- **Company:** kAIgentic
- **Location:** Bengaluru, India
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-22
- **Last confirmed live:** 2026-10-17
- **Apply:** https://jobs.ashbyhq.com/kaigentic/8bdd68bf-1838-4be2-a0cf-422ecf272eb8

## Job description

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

Design and deliver the intelligence layer that turns enterprise process knowledge, documents, interviews, system logs, into a governed, provenance-carrying process ontology, and the AI systems that extract, consolidate, ground, and continuously learn from it. Ensure every output is evidence-backed; hallucination is a product failure, not a metric.

## What You’ll Do

- Build end-to-end pipelines for ingesting complex documents, handling layouts, tables, and scanned diagrams, and generate robust embeddings for long-form content
- Design schema-constrained LLM extraction frameworks using typed schemas, validation loops, and automated repair/re-prompt cycles
- Own retrieval engineering solutions, integrating hybrid search, reranking, and query expansion to surface relevant context efficiently
- Deliver knowledge-graph construction and entity resolution pipelines, modeling property-graphs in Neo4j or equivalent stores and enabling GraphRAG retrieval
- Improve grounding mechanics by integrating terminology stores and retrieval-in-the-loop generation to ensure evidence-backed outputs
- Collaborate with cross-functional product and research partners to define evaluation datasets, grading rubrics, and regression gates, feeding field insights back into the roadmap
- Build multi-agent orchestration using planner/worker patterns and tool routing on native SDKs, ensuring seamless state sharing and coordination
- Own MCP and agent-to-agent integration, implementing secure contracts, authentication boundaries, and context passing between services

## What You’ll Bring

- Proven expertise delivering production-grade AI solutions in Python, with strong typing, test coverage, and async pipeline design
- AI-native velocity as a default mode of working
- Deep knowledge of large-language-model prompting, schema-driven extraction, and automated repair loops
- Mastery of retrieval techniques, including dense embeddings, hybrid search, reranking, and query expansion
- Experience building and operating property-graph databases such as Neo4j, and implementing entity resolution and GraphRAG pipelines
- Hands-on competence with grounding architectures, terminology stores, and retrieval-in-the-loop generation
- Proficiency in multi-agent orchestration frameworks (e.g., LangGraph, OpenAI Agents SDK) and secure MCP or A2A integration patterns
- Track record of defining evaluation datasets, constructing graders, and establishing regression testing with tracing tools like Langfuse
- Strong judgment to balance research ambition with product constraints, and clear communication with engineers, product managers, and senior stakeholders
- Master's degree in Computer Science, AI, or a related field (or equivalent practical experience), with 3+ years of relevant experience.

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.

## About kAIgentic

## Company Overview
- **One-liner**: kAIgentic builds an enterprise “Intelligence Layer” that captures tacit knowledge and deploys governed, autonomous AI agents to accelerate transformation in complex, regulated environments.
- **Entity Type**: Private (Majority-owned by Sumitomo Mitsui Financial Group)
- **Headquarters**: Singapore (9 Straits View, #06-07 Marina One West Tower, Singapore 018937)
- **Founded**: August 2025
- **Founders**: Ahmed Jamil Mazhari (CEO; former President of Microsoft Asia, former leader at GE and Genpact)

## Core Business
- **Primary Industry**: Enterprise AI / Agentic AI Software
- **Target Customers**: Large, complex enterprises in regulated industries (starting with financial services); B2B, Enterprise
- **Mission**: Liberate people from the constraints of legacy systems and incremental improvement by enabling companies to evolve as fast as technology.

## Products & Services
- **kAIgentic Platform (Enterprise Intelligence Layer)**: A software platform that captures tacit human, process, and system knowledge; composes reliable multi-agent AI solutions; and runs them in production with full observability, governance, and audit controls. It enables real-time reasoning, decision-making, and autonomous action beyond simple automation.
- **Dual Transformation Engine**: A strategy combining an internal engine (embedding AI agents across SMBC Group’s core businesses) with an external business engine (productizing those learnings for other corporate clients), using SMBC Group as “customer zero.”
- **Infinity Kaizen**: A continuous feedback loop framework that uses operational data and business KPIs to repeatedly review models, rules, and processes, driving ongoing improvement in quality, speed, and cost.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (privately held)
- **Key Metric**: Total Funding – $10 million investment from SMBC Group (announced November 2025), which acquired a majority stake.
- **Notable Investors/Partners**: Sumitomo Mitsui Financial Group (SMFG/SMBC Group) – founding partner, majority owner, and first customer.
- **Growth Signals**:
  - Launched in August 2025 and immediately secured a $10M investment and a founding enterprise customer (SMBC Group).
  - Headquartered in Singapore with core engineering operations in Bengaluru, India.
  - Actively hiring across multiple senior roles (Principal Engineer, SDE III, Product Leader) as of early 2026.
  - Leadership team has global experience across Asia, Europe, and North America with a track record of scaling technology businesses.

## Competitive Advantages
- **Enterprise-Grade by Design**: Security, compliance, and responsible AI guardrails are built into every layer from day one, making the platform ready for the most regulated environments.
- **Proven in Production**: Built with and for a global financial services leader (SMBC Group) as founding partner, providing deep domain expertise and live telemetry.
- **Dual Engine Model**: The inside-out/outside-in approach (transforming a large enterprise while productizing that transformation for others) creates a unique learning loop that de-risks and accelerates innovation.
- **Focus on Tacit Knowledge**: Differentiates by capturing the unwritten, un-documented knowledge of knowledge workers, not just automating explicit processes.
- **Japanese Roots, Global Ambition**: Leverages Japan’s international ecosystem as a starting point, an often-overlooked source of transformation potential.

## Strategic Focus
- **Current Priority**: Embed AI agents across every workflow and operation within SMBC Group to establish it as an “AI-Leading Company,” while simultaneously building the external product and go-to-market engine.
- **Growth Direction**: Scale the platform from financial services into any knowledge-driven, complex enterprise environment globally. The long-term goal is to close the gap between what AI technology can achieve and what large organizations can safely absorb.

## Why Work Here
- **Culture & Mission**: A high-impact, mission-driven environment focused on liberating people from legacy systems. The company emphasizes continuous improvement (“Infinity Kaizen”) and a dual engine of innovation.
- **Work Policy**: Hybrid – roles are listed as hybrid, with offices in Singapore, Bengaluru (India), and likely other locations.
- **Engineering Culture**: Building at the frontier of agentic AI for enterprise. Roles involve designing durable, observable orchestration for long-running AI workflows (e.g., Temporal-based systems), LLM orchestration, and solving complex reliability and governance problems in production.
- **Notable Perks/Highlights**: Opportunity to work on cutting-edge agentic AI from day one, directly impacting a major global financial institution. The team is small (20 employees as of early 2026) but well-capitalized and backed by a deep-pocketed strategic partner, offering startup velocity with enterprise stability.

## Sources
1. [kaigentic.com](https://kaigentic.com/)
2. [smfg.co.jp](https://www.smfg.co.jp/news_e/pdf/e20251113_01.pdf)
3. [inc42.com](https://inc42.com/buzz/ex-microsoft-apac-president-launches-kaigentic-with-10-mn-funding-to-build-ai-for-global-enterprises/)
4. [builtin.com](https://builtin.com/company/kaigentic/jobs)
5. [recordowl.com](https://recordowl.com/company/kaigentic-pte-ltd)

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