anupdavin

tailor-lead-cloud-native-spring-ai-engineering

Auto-induced behavioral skill for scoring and tailoring Lead Cloud-Native & Spring AI Engineering job applications (Critic Verified Score: 95/100).

anupdavin 0 Updated 3w ago
GitHub

Install

npx skillscat add anupdavin/autonomous-career-engine/tailor-lead-cloud-native-spring-ai-engineering

Install via the SkillsCat registry.

SKILL.md

Induced Skill: Lead Cloud-Native & Spring AI Engineering Application Strategy

Automatically induced from successful execution trace on 2026-09-27T03:56:50.675827+00:00 (Critic Score: 95/100).

When to Activate

Activate this skill whenever evaluating or tailoring resumes/outreach for Lead Cloud-Native & Spring AI Engineering or similar roles (e.g., Lead / Staff Software Engineer — Java 21, Spring Boot 3, Cloud-Native & Spring AI).

Winning Behavioral Strategy

Connect FinVault Digital Bank (Singapore / Hybrid / Remote APAC)'s stack (Java 21, Spring Boot 3, Kubernetes, Kafka) to Meena Kannan's Knowledge Graph node 'VRLS 2.0 Cloud-Native Microservices & AI Modernisation (NCS Singapore / LTA)' (USES_SKILL -> Java 21 & Spring Boot 3.x / WebFlux / Security, USES_SKILL -> AWS Government Cloud, EKS, ECS, Kubernetes, Helm, Istio Service Mesh, USES_SKILL -> Apache Kafka, Kafka Streams, KEDA Autoscaling, Redis, Outbox & Saga, USES_SKILL -> Spring AI, RAG Pipelines, MCP Servers, Claude API, Agentic Workflows), anchoring with 3 production metrics: AWS GovCloud VRLS 2.0 scale, -40% API reduction, and 15m->real-time Kafka + Spring AI/MCP leadership.

Reference High-Scoring Application Pitch

**Tailored Executive Pitch — Meena Kannan for Lead / Staff Software Engineer — Java 21, Spring Boot 3, Cloud-Native & Spring AI @ FinVault Digital Bank (Singapore / Hybrid / Remote APAC)**
- **Cloud-Native & Microservices Leadership (9+ Yrs)**: Architected **VRLS 2.0 at NCS / LTA Singapore**, modernising a legacy Java monolith into **Java 21 + Spring Boot 3** microservices on **AWS Government Cloud (EKS/ECS)** with **Istio mTLS**, **Apache Kafka + KEDA autoscaling**, **Redis**, and **ArgoCD GitOps** serving millions of users.
- **Quantified Engineering Impact**: Cut redundant API calls by **~40%** leading the **Angular 13 → 18 (NgRx/RxJS)** migration at LTA; slashed ML execution-reporting delays from **15+ mins to near real-time** using Kafka event streams at **BlackStraw.AI**; engineered a **sub-500ms** AI + Drools BRMS compliance microservice at **Wolters Kluwer**.
- **AI-Augmented Engineering (`Spring AI` / `RAG` / `MCP`)**: Rolled out **GitHub Copilot agentic workflows** and prototyped **Spring AI, RAG vector pipelines, Model Context Protocol (MCP) servers, and Claude API** integrations with PDPA-compliant governance.