Qualifications & ExperienceSoftware Engineering Foundation
Expert Software Engineering: 15+ years in software engineering. You are an expert in Java or Scala (distributed systems focus) and Python.
Systems Architecture: Deep experience building extensible frameworks, high-throughput APIs, and libraries used by other developers. You prioritize building “software-defined infrastructure” over manual configuration.
Agentic Development & Emerging Trends (Specialized Plus)
Agentic Design Patterns: Hands-on experience with the latest trends in agent development, such as Multi-Agent Orchestration (using frameworks like LangGraph or CrewAI) and the transition from static RAG to Agentic RAG.
Protocol Interoperability: Knowledge of the Model Context Protocol (MCP) and other emerging standards that allow AI agents to interact with diverse data sources and tools in a plug-and-play manner.
AI-Ops Integration: Experience building “AI-native” CI/CD features, such as automated LLM-based evaluations (evaluating agent reasoning paths in the build pipeline) and Automated Root-Cause Analysis for system failures.
Human-in-the-Loop (HITL): Understanding of how to build automated workflows that pause agent actions for human approval, ensuring safety and governance for autonomous systems.
CI/CD & Platform Ops Mastery (Core Focus)
GitOps & Continuous Delivery: Expert-level experience with GitOps workflows (e.g., ArgoCD or Flux) to ensure that all platform configurations—including AI prompt templates and model parameters—are versioned, audited, and automatically reconciled.
Infrastructure-as-Code (IaC) at Scale: Mastery of Terraform. You don’t just write scripts; you build modular, reusable libraries that enforce organizational security and cost-efficiency standards across hundreds of cloud accounts.
Modern CI Pipelines: Proficiency in designing complex pipelines (e.g., GitHub Actions, GitLab CI) that integrate automated testing, security scanning, and deployment gates for high-availability systems.
Unified Observability: Experience with OpenTelemetry (OTel) to build deep visibility into distributed systems. You focus on tracking both system performance and business-centric AI metrics (e.g., success rates of autonomous tasks).
Cloud Platform Expertise (AWS & Azure)
Cloud Console & Service Mastery: Deep proficiency in navigating and configuring the AWS and Azure Management Consoles. You have a comprehensive understanding of how to architect, secure, and optimize core services (IAM, EC2/VMs, S3/Blob, and specialized AI/ML service suites) natively within both ecosystems.
Cloud-Agnostic Abstraction: Proven ability to build platform layers that bridge AWS and Azure, allowing for seamless deployment and management across a multi-cloud environment.
Governance & Cost Optimization: Experience using cloud-native tools (AWS CloudWatch, Azure Monitor, Cost Explorer) to manage platform health, security posture, and spend at an enterprise scale.
Leadership & Education
Influence: A proven track record of “leading by influence”—driving adoption of new technologies across multiple autonomous teams.
Communication: Ability to communicate complex architectural trade-offs (e.g., “Latency vs. Consistency”) to both C-suite executives and engineers.
Education: Bachelor’s or Master’s degree in Computer Science (Distributed Systems focus) preferred, or equivalent deep industry experience.