Lead Product Support Engineer

kAIgentic

Lead Product Support Engineer diagnosing integrations, APIs, logs, and agent behavior for kAIgentic’s enterprise agentic AI platform. Helping regulated customers deploy and scale reliable workflows.

Posted 8/7/2026full-timeBengaluru • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in diagnosing customer issues related to code, APIs, and systems, while effectively communicating technical concepts to both technical and non-technical stakeholders. Proficient in building documentation and tooling to enhance customer success and operational efficiency.

Highest-signal resume keywords

Technical Support PracticesAPI UnderstandingPython ProgrammingObservability ToolingCustomer-Facing Technical Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Code TracingSystems ThinkingDebuggingIntegration DiagnosisLLM KnowledgeTechnical DocumentationWorkflow AnalysisCustomer Issue InvestigationOperational JudgmentAmbiguity Management

Soft Skills

Customer-Focused ApproachEffective CommunicationIndependent Problem SolvingAsynchronous CollaborationAdaptability

Tools & Technologies

APM ToolsObservability ToolsDistributed SystemsAgentic AI Systems

Industry Keywords

Financial ServicesEnterprise OperationsEarly-Stage Company

Tech Stack

Tools & technologies

Distributed SystemsPython

About the role

Key responsibilities & impact

Investigate customer issues involving code, APIs, logs, and deployed systems
Read API traces, follow execution paths through workflows, and identify breakdowns
Work with customers to understand what they are building with agents
Escalate issues to engineering with precise reproduction steps, data, and context
Build tooling and documentation, evolving it into a knowledge base
Help customers achieve value through technical deep dives, implementation guides, and prompt restructuring
Feed recurring customer problems and product gaps back to the team
Diagnose integration failures, unexpected agent behavior, and workflow scaling issues
Define technical support practices for an early-stage agentic AI company

Requirements

What you’ll need

Experience in technical work spanning systems thinking, customer communication, and operational judgment
Ability to read, understand, trace, and explain code
Comfort with APIs, logs, distributed systems, and debugging ambiguous issues
Working knowledge of how LLMs work, their strengths, and predictable failure modes
Ability to distinguish hallucinations, prompt issues, temperature problems, and knowledge cutoff problems
Ability to communicate with both technical founders and business operations professionals without oversimplifying or overusing jargon
Comfort with ambiguity and independently proposing solutions or challenging assumptions
Customer-focused approach aimed at customer success rather than simply closing tickets
Ability to work asynchronously and independently across customer schedules, systems, and time zones
Prior customer-facing technical experience at an early-stage company is a strong plus
Python or a similar programming language is a strong plus
Experience with observability tooling, APMs, or infrastructure debugging is a strong plus
Experience building or shipping an LLM-based product is a strong plus
Familiarity with financial services or enterprise operations is a strong plus

Benefits

Comp & perks

Ownership from Day One
Learning and growth alongside seasoned leaders from leading enterprises
Global collaboration with teams across Singapore, India, Japan, Europe, and the US
Psychological safety, transparent disagreement, and disciplined experimentation
Opportunity to shape the product, culture, and customer outcomes
Work on enterprise infrastructure with real consequences and mission-critical, regulated environments