Principal SDE - Cloud, Platform & Agentic AI

Job Requirements

Enterprise Architecture & Platform Leadership

Define and evolve reference architectures for distributed, low‑latency, high‑TPS systems deployed on AWS and Kubernetes (EKS). Serve as a final technical escalation point for complex architectural and system design decisions across multiple teams. Lead architectural trade‑off decisions spanning compute, networking, data, resiliency, observability, and cost—with explicit SLAs/SLOs. Own and evangelize non‑functional requirements (latency, throughput, availability, scalability, operability, security, cost efficiency). Drive architectural consistency while enabling team‑level autonomy through clear patterns and guardrails.

Deep Hands‑On Engineering & Validation

Design and review critical execution paths in Java‑based microservices (Spring Boot, gRPC, REST). Build sophisticated POCs and spike solutions to de‑risk architecture decisions and emerging technologies before broad adoption. Perform advanced production debugging across application, JVM, Kubernetes, and AWS layers. Model “prototype‑first” engineering—validating ideas experimentally before standardization. Remain hands‑on enough that designs are grounded in real operational constraints.

Cloud & Kubernetes Expertise (AWS / EKS)

Architect and guide large‑scale AWS environments leveraging:

EKS, EC2, ALB/NLB, VPC, IAM, Auto Scaling Logging, metrics, distributed tracing, and alerting

Define Kubernetes platform patterns:

Pod and node design HPA and autoscaling strategies Multi‑AZ and resilience models Safe rollout, rollback, and canary strategies

Influence security‑first, cost‑aware, and operationally efficient cloud designs at scale.

Agentic AI & AI‑Augmented Engineering

Architect and prototype Agentic AI–driven engineering systems embedded into the SDLC. Drive adoption and safe usage of GenAI tools such as GitHub Copilot and custom AI agents to:

Accelerate development and refactoring Improve code quality, reviews, and test coverage Reduce cognitive load for engineers

Experiment with AI‑enabled workflows across:

Design → Build → Test → Deploy → Operate