Go backLocation: Bangalore, India
Employment Type: Full-time
Experience: 15+ years
About kAIgentic
kAIgentic is a Singapore-headquartered startup, with presence across Singapore, India and Japan, on a mission to help enterprises evolve as fast as technology by turning their hidden know-how into safe, AI-powered operations. Most large organizations struggle to transform. Their tacit knowledge lives in people’s heads; systems are fragmented, and risk appetite is low. Our platform captures how work happens, designs better workflows, and runs them as governed by agentic operations. The result: organizations that continuously improve, instead of changing in slow, risky bursts.
We’re backed by SMBC Group as our founding partner and “customer zero”, and our platform is already being proven in one of the world’s most complex, regulated environments. That gives us access to real problems, real data, and real impact from Day 1.
The Role
As Principal Engineer on the AI Research team, you will define how enterprise AI achieves the accuracy, auditability, and reliability that regulated industries demand—and you will deliver on that vision in production. This is not a research-for-research's-sake role: you are the architect and builder of kAIgentic's intelligence layer strategy—determining what methods we adopt, what we build ourselves, and how we translate advances in AI research into production systems that banks can trust. You will shape org-wide standards for evaluation, hallucination elimination, and knowledge extraction, while acting as kAIgentic's external voice on enterprise AI in financial services.
What You'll Do
- Own the long-term technical vision for kAIgentic's intelligence layer, including retrieval architecture, knowledge extraction, and hallucination mitigation strategy across all product lines
- Set org-wide standards for AI evaluation methodology—the frameworks, metrics, and thresholds that define what 'reliable enough for enterprise' means at kAIgentic
- Define the research-to-production pipeline: how kAIgentic systematically evaluates emerging AI techniques, de-risks adoption, and ships them to regulated environments
- Solve the hardest open problems in enterprise AI reliability: multi-hop reasoning grounding, cross-document consistency, and real-time self-correction at production latency
- Establish kAIgentic's external technical identity in enterprise AI through publications, benchmark contributions, and industry partnerships
- Lead evaluation and integration of foundation model providers and emerging model families
- Mentor Staff and Lead Engineers on AI system architecture and research methodology
- Optionally lead a small embedded research engineering crew (2–4 engineers) driving your highest-leverage AI platform programs, with technical direction owned by you and people management owned by the engineering manager
What You'll Bring
- 15+ years in software engineering with deep AI/ML focus, including significant experience deploying AI in regulated or high-stakes environments
- Recognized thought leadership in applied AI—publications, benchmark contributions, open-source AI tooling, or equivalent demonstrated impact
- AI-native velocity as a default mode of working (mandatory)
- Expert-level Python; strong knowledge of Go a plus
- Deep expertise in 5+ of the following:
- RAG architecture and retrieval systems at enterprise scale, including hybrid search, multi-stage reranking, and adaptive retrieval strategies
- Document AI, enterprise NLP, and complex layout understanding
- Hallucination detection and mitigation at the architectural level (not just prompt-level)
- LLM evaluation methodology including systematic grounding measurement, adversarial testing, and regression tracking
- Knowledge extraction and structured output generation from unstructured enterprise processes
- AI observability and debugging at model behavior, retrieval quality, and system performance levels
- Fine-tuning, RLHF, and alignment techniques for domain-specific enterprise applications
- Guardrails and output validation systems for regulated deployment
- Proven track record of AI systems operating in production in high-stakes environments (finance, healthcare, legal)
- Ability to evaluate foundation model capabilities and limitations with genuine technical depth
- Strong communication skills for both technical peers and business stakeholders including regulators and enterprise CISOs
Why join kAIgentic?
We’re a global team of builders who thrive in ambiguity, care deeply about customers, and believe in the power of AI to reshape enterprise work.
We look for people who:
- Bring technical excellence and customer empathy together.
- Are entrepreneurial and excited to work on zero-to-one problems.
- Lead with ownership, integrity, and collaboration.
- want to shape not just a product, but a new category of enterprise AI.
Working here means being surrounded by peers who challenge assumptions, celebrate progress, and build with courage and care.
What It Feels Like to Work at kAIgentic?
- Innovation at Scale: Combine startup agility with enterprise-grade challenges.
- Ownership from Day One. Your work directly shapes product, culture, and customer outcomes.
- Learning & Growth – Work with seasoned leaders (ex-Microsoft, AWS, UiPath, Wipro, GE, Genpact) who’ve built and scaled global businesses.
- A culture of trust and psychological safety where experimentation is encouraged.
- Global collaboration across Singapore, India, Japan, Europe, and the US.
- A shared mission to build something the world hasn’t seen before: AI Agents that continuously improve how enterprises run.
