Job Description: Engineering Manager (Systems, Scale & AI-Augmentation)
Experience:
14+ Years
Core Focus:
Scalable Architecture, Cost-Optimization, and AI-Driven Development
Role Type:
Senior Technical Leadership
The Mission
We are looking for a
Senior Engineering Manager
who bridges the gap between decade-long architectural wisdom and the future of AI-driven engineering. You have spent 14+ years building systems that scale, and you now view
Artificial Intelligence
as the primary lever to accelerate that process without increasing headcount or complexity.
You are the guardian of our technical integrity. You believe that "less is more" and that the most scalable systems are the simplest. You will lead our team to embrace AI-augmented workflows while ensuring our infrastructure remains lean and our automation is absolute.
Key Responsibilities
1. AI-Driven Development & Velocity
SDLC Transformation:
You will own the integration of AI tools (e.g., GitHub Copilot, Cursor, AI-driven refactoring) into our daily rituals. Your goal is to achieve a 2x-3x increase in developer throughput without sacrificing quality.
Prompt Engineering for Architects:
You will guide the team in using LLMs for architectural brainstorming, threat modeling, and generating complex test suites, ensuring that AI-generated code meets our strict standards for
simplicity and scale
.
AI Governance:
You will establish the "Rules of Engagement" for AI, ensuring security, data privacy, and that the team maintains deep "human-in-the-loop" understanding of every line of code shipped.
2. Scalability & Architectural Integrity
Scalable Systems Design:
Architect systems that scale linearly. You will identify and eliminate bottlenecks in data flow, concurrency, and state management.
The "KISS" Advocate:
You have the battle-scars to know when a simple SQL database beats a complex microservices mesh. You will veto over-engineered solutions to keep the codebase maintainable.
Observability:
Implement "predictive observability" using AI to monitor system health and detect anomalies before they become outages.
3. Fiscal Engineering (Cost-Optimization)
Cost-Aware Architecture:
You treat the cloud bill as a performance metric. You will lead the team in optimizing resource utilization—especially as AI workloads or high-scale traffic increase—to ensure maximum ROI on every dollar spent.
Operational Efficiency:
Use AI-driven insights to identify redundant code, inefficient queries, and unused resources that impact our burn rate.
4. Extreme Automation
Self-Healing Tests:
Architect an automation framework where AI assists in generating and maintaining test cases.
CI/CD Excellence:
Ensure a "No-Manual-Ops" environment. You believe that if a human has to click a button to deploy, the system is broken.
Technical Expertise Required
14+ Years in Systems Engineering:
Mastery of backend technologies and distributed systems.
AI-First Mindset:
Proven experience in leveraging AI coding assistants and agents to speed up development cycles.
Distributed Systems:
Expert knowledge of load balancing, caching strategies, message brokers (Kafka/RabbitMQ), and database sharding.
The "Lead from the Front" Ability:
You can still jump into a PR or a debug session and show the team how to solve a $10,000/month infrastructure leak.
