Performance Engineering Lead.

Who We Are:
Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.  

About the Product:
ProteanTecs is redefining how advanced electronics perform in real-world conditions. Built on deep data from Universal Chip Telemetry (UCT), our client’s platform delivers predictive insights at scale across the full chip lifecycle. This isn’t a typical SaaS system – they’re operating across edge devices, complex ML pipelines, petabyte-scale telemetry data, and mission-critical cloud infrastructure. Performance here isn’t about shaving milliseconds – it’s about enabling global tech companies to prevent downtime, increase yields, and improve reliability in real time.

About the Role:
As a Performance Engineering Lead, you’ll take full ownership of proteanTecs’ performance strategy across the entire technology stack: from edge compute and ML workloads to cloud-based analytics and customer-facing dashboards.

You will design and lead performance testing across the entire platform from data upload and backend processing, through machine learning workloads, to BI dashboards and visualization layers. This role combines hands-on technical work with strategic leadership, shaping how performance, scalability, and stability are measured, tested, and continuously improved throughout our software lifecycle.

Your work will directly affect how customers interact with ProteanTecs’ platform and how the most advanced semiconductor systems in the world are monitored and optimized.

Key Responsibilities:

• You’ll own the performance layer of a deep-tech platform with massive real-world impact
• Design and execute platform-wide performance testing (load, stress, longevity)
• Identify bottlenecks across backend services, databases, ML pipelines, and dashboards
• Optimize microservices, APIs, and cloud environments (AWS, Kubernetes) for speed and efficiency
• Tune database performance for ingestion, queries, and indexing
• Improve ML workload efficiency (training, inference, resource use)
• Boost performance of dashboards and large-scale data visualizations
• Integrate automated performance testing into CI/CD workflows
• Define and track KPIs, SLAs, and reliability metrics
• Act as a company-wide performance advocate, promoting best practices across teams
• Partner with Product, Dev, DevOps, Analytics, and Machine Learning teams to identify, isolate, and resolve performance issues. 
• Mentor teammates and raise the engineering bar for scalability and stability.
• Lead initiatives like Continuous Performance and “Performance as a Service”.

Required Competence and Skills:

• 6+ years of experience in performance engineering, backend optimization, or large-scale cloud systems. 
• Proven experience designing, executing, and analyzing performance, load, and stress tests. 
• Strong Python skills (core language for test automation and analysis). Java background acceptable if willing to switch to Python.
• Proven experience in testing and optimizing systems running in Kubernetes clusters.
• Hands-on experience with cloud environments (AWS, GCP, or Azure).
• Solid background in performance testing of distributed systems and microservices.
• Experience with monitoring/observability tools (Prometheus, Grafana, etc.).
• Knowledge of database performance (Vertica, MySQL, and Elasticsearch).
• Strong analytical mindset and the ability to collaborate across multiple engineering disciplines.
• Excellent communication and coordination skills – able to lead initiatives across teams.
• Familiarity with machine learning or MLOps workloads – understanding model training, inference, and resource utilization from a performance perspective.

Nice to have:

• Experience leading performance and reliability initiatives or teams. 
• Strong understanding of big data systems, distributed architectures, and scalability challenges. 
• Understanding of frontend and BI dashboard performance, including query efficiency, caching, and rendering optimization.
• Experience in testing and optimizing Tableau dashboards and Vertica performance. 
• Familiarity with data pipelines, parquet-based processing, or ETL systems. 
• Knowledge of machine learning infrastructure (MLRun). 
• Proven success in building or contributing to internal performance frameworks.

Why Us?

We provide 20 days of vacation leave per calendar year (plus official national holidays of the country you are based in).

We provide full accounting and legal support in all countries in which we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.