Sr. Director, Cloud Engineering

TraceLink is seeking a strategic and hands-on Senior Director of Cloud Engineering to lead a multi-disciplinary organization spanning Site Reliability Engineering (SRE), Performance & Tools Engineering, and Release Engineering. This role is critical to ensuring the scalability, reliability, and operational excellence of TraceLink’s cloud-native SaaS platform, while also owning the infrastructure behind both internal and customer-facing AI capabilities.

The Director will be the single-threaded owner of our internal suite of AI-enabled tools for engineering productivity, as well as responsible for the DevOps and infrastructure support for external AI features integrated into the Opus platform, such as LLM-powered agentic functionality.

They will drive initiatives that enable AI-powered operational intelligence, cost-optimized infrastructure, and high-velocity product delivery across a globally distributed engineering team.

Responsibilities:

• Act as a Single Threaded Owner (STO) for infrastructure & operational excellence  and lead a global organization across three primary areas:

  • SRE, with an SRE Manager and team focused on reliability, observability, incident response, and cloud operations

  • Performance & Tools, building tooling for automated testing, test orchestration, system health monitoring, and integration testing

  • Release Engineering, responsible for CI/CD tooling, release orchestration, and deployment automation

• Own and evolve TraceLink’s internal suite of AI-enabled tools designed to enhance developer productivity and platform insight

• Play a leadership role in DevOps and infrastructure operations for AI capabilities integrated into TraceLink’s Opus platform, including support for LLM-based workflows, inference pipelines, and secure model interactions

• Evaluate and adopt emerging technologies aligned with the company’s product vision and technical architecture

• Partner with the CISO, architecture, and product teams to align cloud practices with security, compliance, and business goals

• Drive maturity in infrastructure as code, observability (OpenTelemetry, Prometheus, Grafana, Jaeger), and release automation (Jenkins, Flux-CD, Env0, CodeBuild)

• Lead the design and rollout of AI-driven anomaly detection, telemetry pipelines, and proactive system health monitoring

• Extend CI/CD and integration testing systems to support performance testing, distributed tracing, and alerting workflows

• Be a major contributor to efforts to improve product quality through improved automated testing

• Champion cost optimization initiatives, including efficient AWS resource usage (Karpenter, Spot Instances, serverless), and align to target COGS metrics

• Set high standards for reliability, latency, availability, and scalability of core systems

• Oversee deployment health, platform smoke tests, and post-deployment validation strategies

• Monitor and report on platform KPIs, system uptime, alerting noise ratios, and MTTR

• Lead incident response strategies and reduction of manual toil through automation and self-service tools

• Hire, mentor, and grow high-performing engineering managers and technical leaders

• Align team OKRs with broader engineering and company goals

• Foster a culture of engineering rigor, continuous improvement, and cross-functional collaboration

Qualifications:

Required:

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience

• 5+ years in engineering leadership roles managing multiple cross-functional DevOps/SRE/tooling teams

• Deep experience with cloud-native architecture, especially AWS services, infrastructure-as-code, CI/CD systems, and observability platforms

• Proven success running SaaS at scale, including performance, reliability, and cost optimization

• Hands-on experience with tools such as Terraform, Helm, Docker, Kubernetes, Prometheus, ELK, Redis, Kafka, Karpenter, Jenkins, OpenTelemetry, Grafana, Env0, CodeBuild

• AWS Bedrock or equivalent managed foundation model platforms

• Experience supporting AI/ML-enabled applications, including inference pipelines and secure LLM integration

• Experience with high-performance inference runtimes such as KServe, vLLM, TensorRT-LLM, TGI, or Envoy AI Gateway

• Techniques for optimizing inference performance and cost, including KV Cache management, prompt caching, model quantization, and batching strategies

• Clear understanding of security practices, DevSecOps, and compliance (e.g., SOC-2, ISO27001)

• Excellent communication and stakeholder management skills

Preferred:

• Advanced degree in Engineering or related field

• Experience with regulated industries (e.g., healthcare, pharma, or life sciences)

• Familiarity with reactive frameworks and modern Java/JavaScript application stacks