Head Of Engineering

Job Summary

The Head of Engineering at AUMET leads the design, scaling, and security of the technology platform supporting AI-driven solutions. This role involves overseeing distributed systems, cloud infrastructure, backend engineering, and DevOps to enable enterprise-scale AI operations.

Responsibilities

• Design and scale distributed, fault-tolerant systems for complex multi-agent AI workflows.
• Architect APIs, microservices, API gateways, and external integrations for high performance.
• Optimize relational, NoSQL, and vector databases for high-volume AI workloads.
• Develop secure, multi-tenant SaaS architectures with data and workload isolation.
• Lead cloud infrastructure management across AWS, GCP, or Azure, including containerization with Docker and Kubernetes.
• Implement Infrastructure as Code, CI/CD automation, and monitoring using tools like Grafana and New Relic.
• Establish AI governance policies, security controls, and compliance with frameworks such as SOC 2, ISO 42001, NIST AI RMF, and GDPR.
• Lead and mentor engineering teams, set architectural standards, and align technical strategy with business goals.

Must haves

• Experience designing and scaling distributed, fault-tolerant, cloud-native systems.
• Expertise in backend architecture, microservices, API design, and database optimization.
• Hands-on experience with SQL, NoSQL, and vector databases.
• Knowledge of high-concurrency systems and distributed messaging technologies like Kafka, RabbitMQ, Redis, AWS SQS, Celery, or Temporal.
• Proficiency with cloud platforms AWS, GCP, or Azure.
• Experience with Docker, Kubernetes, Infrastructure as Code (Terraform), and monitoring tools such as Grafana and New Relic.
• Understanding of LLM APIs, prompt engineering, and production challenges of AI systems.
• Experience implementing AI governance, security controls, model risk management, and compliance frameworks.
• Proven engineering leadership including mentoring and driving technical strategy.

Nice to haves

• Experience with workflow orchestration tools like 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.

What the company offers

• Lead infrastructure development for next-generation agentic AI systems.
• Influence product scalability, reliability, and security through architectural decisions.
• Work at the intersection of AI innovation, cloud engineering, and enterprise technology.
• Shape engineering strategy and build a high-performing team delivering impactful solutions.

We refresh listings regularly, but some roles close early on the source platform.