Correlation & Causality Engineer|Hybrid AI & Observability

Avaloq; Makati; Hybrid; PHP 5,732,000 - 8,917,000; Full time

Job summary

Avaloq wishes to hire a Correlation and Causality Engineer to design and implement solutions that transform observability data into actionable insights. You will combine software engineering with applied AI to build correlation, inference, and root-cause systems that operate on large volumes of logs, metrics and traces.

The role emphasizes production-ready services in Java and Python and involves LLM-based tooling and local/on-prem deployment.

Qualifications

• Bachelor’s degree or equivalent experience in a related field.
• Strong software development skills in Java and Python, solid testing and engineering practices.
• Strong AI expertise with data‑driven models and causal inference concepts.
• Hands-on experience with LLMs and tooling (RAG, embeddings, vector stores).
• Experience with running/fine‑tuning AI models locally/on‑prem and GPU awareness.
• Proficiency with ML libraries (pandas, NumPy, scikit-learn, PyTorch/TensorFlow).
• Solid DevOps skills: Git, CI/CD pipelines, automation tools (Jenkins, GitLab/GitHub).
• Good knowledge of Docker and Kubernetes; observability stacks (Prometheus, Grafana).
• IaC familiarity (Terraform) and cloud platforms (AWS, Azure, OCI, GCP).
• Ability to translate business needs into AI-driven solutions.

Responsibilities

• Design and implement correlation, root-cause analysis and inference solutions across logs, metrics and traces.
• Develop data-driven models including anomaly detection and time-series analysis.
• Productionize models and services in Java and Python for scalable deployment.
• Explore and build LLM-based applications (RAG, agents, tool calling, embeddings).
• Deploy AI models on local/on-prem infrastructure with performance and cost awareness.
• Collaborate with DevOps, SRE, product and operations to maximize value from AI.
• Define metrics and evaluation processes for AI-based solutions.

Skills

Java

Python

AI

LLMs

Prometheus

OpenTelemetry

Grafana

Docker

Kubernetes

Git

CI/CD

Data science

Time series

Causal inference

DevOps

Education

Bachelor’s degree in Computer Science, Engineering, Data Science or related field

Tools

Jenkins

GitLab

GitHub

LangChain

Job description

Avaloq wishes to hire a Correlation and Causality Engineer to design and implement solutions that transform observability data into actionable insights. You will combine software engineering with applied AI to build correlation, inference, and root-cause systems that operate on large volumes of logs, metrics and traces.

The role emphasizes production-ready services in Java and Python and involves LLM-based tooling and local/on-prem deployment.