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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading AI execution platforms with a focus on reliability, governance, and compliance within regulated banking environments. Capable of building high-performing engineering teams and translating complex product requirements into actionable engineering strategies.
Highest-signal resume keywords
AI Execution Platform LeadershipDistributed Workflow OrchestrationGo ProgrammingPython ProgrammingReliability Engineering
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI-Native DevelopmentDurable Execution EnginesMulti-LLM GovernanceIncident ManagementSLO DesignAudit LoggingModel Lifecycle ControlsRegulatory ComplianceHigh-Availability SystemsDeployment Architectures
Soft Skills
Strategic JudgmentTeam BuildingContinuous Improvement
Tools & Technologies
Deployment PipelinesObservability ToolsIncident Response Systems
Industry Keywords
Regulated BankingZero-Trust SecurityCompliance-By-DesignMulti-Tenant Environments
Tech Stack
Tools & technologiesPythonGo
About the role
Key responsibilities & impact- Define and lead the engineering organization delivering reliable, governed AI-driven execution for regulated banking customers
- Own end-to-end reliability, auditability, and multi-LLM governance
- Define engineering strategy for non-deterministic execution, five-nine reliability, resumable workflows, and human-in-the-loop control
- Lead deployment pipelines operating inside customer-owned, highly regulated infrastructure
- Establish model and LLM governance, audit trails, and multi-LLM policy enforcement across the execution gateway
- Build cross-functional teams aligning product, security, and SRE practices
- Drive production feedback into the ontology, product enhancements, and roadmap inputs
- Align engineering processes with regulatory audit cycles, observability, incident response, and SLO ownership
- Represent kAIgentic to senior customer and regulator stakeholders
- Build the talent pipeline, hire senior engineers, and establish scalable career paths
Requirements
What you’ll need- Proven expertise leading large-scale AI execution platforms with a track record of delivering high-availability, auditable systems
- AI-native velocity as a default mode of working
- Deep mastery of distributed workflow orchestration, durable execution engines, and LLM integration
- Hands-on experience in Go and Python
- Extensive knowledge of deployment architectures inside bank-owned data centers
- Knowledge of network segmentation, zero-trust security, and compliance-by-design
- Strong background in reliability engineering, SLO design, incident management, and observability for multi-tenant, high-throughput environments
- Experience shaping governance models for multi-LLM ecosystems, including policy enforcement, audit logging, and model lifecycle controls
- Ability to translate ambiguous, evolving product requirements into concrete engineering roadmaps and delivery cadences
- Strategic judgment balancing AI-native development speed with regulatory constraints
- Demonstrated skill in building high-performing engineering organizations, hiring senior talent, and fostering ownership and continuous improvement
Benefits
Comp & perks- Global collaboration with teams across Singapore, India, Japan, Europe, and the US
- Learning and growth alongside seasoned leaders from leading enterprises
- Ownership from Day One
- Psychological safety, transparent disagreement, and disciplined experimentation
- Opportunity to shape a new category of enterprise AI
- Startup velocity combined with enterprise-scale, mission-critical work