Head Of Engineering

AUMET | Build the Infrastructure Powering the Future of Agentic AI At AUMET, we're building next-generation agentic AI systems designed to transform how businesses operate. We're looking for a visionary, hands-on Head of Engineering to architect, scale, and secure the technology platform that powers our AI-driven solutions. This role is ideal for an experienced engineering leader who combines deep technical expertise in distributed systems, cloud infrastructure, backend engineering, and DevOps with a strong understanding of AI systems operating at enterprise scale. You'll lead the engineering foundation that transforms complex, multi-agent AI workflows into reliable, secure, scalable, and production-ready systems. 🔹 Key Responsibilities System Architecture & Backend Engineering Design and scale distributed, fault-tolerant systems capable of supporting complex, asynchronous, multi-agent AI workflows. Architect high-performance APIs, microservices, API gateways, and external integrations. Optimize relational, NoSQL, and vector databases to support high-volume workloads and AI agent memory. Build secure, multi-tenant SaaS architectures with strict data and workload isolation. Design event-driven architectures, message queues, and asynchronous execution systems. Establish scalable infrastructure for LLM integrations, prompt management, caching, and agent state persistence. Cloud Infrastructure, DevOps & Observability Own cloud architecture across AWS, GCP, or Azure. Lead containerization and orchestration strategies using Docker and Kubernetes. Drive Infrastructure as Code, CI/CD automation, and deployment excellence. Implement end-to-end monitoring, alerting, and distributed tracing using tools such as Grafana, New Relic, Prometheus, and OpenTelemetry. Optimize system reliability, API latency, database performance, scalability, and infrastructure costs. AI Governance, Security & Compliance Establish responsible AI governance policies and integrate safety controls into the engineering lifecycle. Develop centralized model registries and governance processes for model versions, LLM dependencies, and prompt templates. Define AI risk classification frameworks based on agent autonomy, data access, and operational impact. Implement automated approval workflows and security controls for models, prompts, and new AI capabilities. Establish runtime guardrails, human-in-the-loop workflows, continuous monitoring, and emergency shutdown mechanisms for high-risk AI actions. Support compliance with relevant frameworks and regulations, including SOC 2, ISO 42001, NIST AI RMF, and GDPR. Engineering Leadership & Technical Strategy Lead, mentor, and scale high-performing backend, infrastructure, DevOps, and AI engineering teams. Establish engineering standards, architectural best practices, and scalable development processes. Collaborate with executive leadership to align technical strategy with business objectives. Balance innovation, system reliability, security, governance, and operational efficiency. Enable engineering teams to deliver AI capabilities rapidly without compromising quality or security. Required Qualifications Proven experience designing and scaling distributed, fault-tolerant, cloud-native systems. Strong expertise in backend architecture, microservices, API design, and database performance optimization. Hands-on experience with SQL, NoSQL, and vector databases. Strong knowledge of high-concurrency systems, asynchronous programming, and distributed messaging technologies such as Kafka, RabbitMQ, Redis, AWS SQS, Celery, or Temporal. Expertise in cloud platforms: AWS, GCP, or Azure. Strong experience with Docker, Kubernetes, and Infrastructure as Code, particularly Terraform. Hands-on experience with observability and monitoring tools, especially Grafana and New Relic. Practical understanding of LLM APIs, prompt engineering, agentic workflows, and the challenges of operating AI systems in production. Experience implementing AI governance, security controls, model risk management, and enterprise compliance frameworks. Demonstrated engineering leadership experience, including mentoring teams and driving technical strategy. Preferred Qualifications Experience with workflow orchestration tools such as Temporal, Airflow, Prefect, or LangGraph. Familiarity with LLM gateways and AI observability platforms such as LiteLLM, LangSmith, Arize, or Helicone. Experience building secure, isolated code-execution environments for autonomous AI agents. Exposure to enterprise AI governance frameworks and production-grade agentic AI architectures. Why Join AUMET? Take a leading role in building the infrastructure behind next-generation agentic AI systems. Drive architectural decisions that directly influence product scalability, reliability, and security. Work at the intersection of AI innovation, cloud engineering, and enterprise-grade technology. Shape engineering strategy and build a high-performing team focused on delivering impactful solutions. #Hiring #HeadOfEngineering #EngineeringLeadership #AI #AgenticAI #CloudEngineering #DevOps #SoftwareArchitecture #Kubernetes #AUMET Show more Show less