AI-Driven Correlation & Causality Engineer

Avaloq Philippines Inc.; Makati; Hybrid; PHP 1,600,000 - 2,400,000; Full time

Benefits offered by this job

Hybrid and flexible working

Job summary

Avaloq Philippines Inc. is seeking a Correlation and Causality Engineer to design and implement AI-powered insights from observability data.

You will combine Java/Python development with data-driven models and LLM tooling to detect correlations, infer root causes, and anticipate incidents before they affect clients. You will work across the observability stack (Prometheus, OpenTelemetry, Loki, Grafana) and collaborate with DevOps, SRE, and product teams to deliver scalable AI solutions on hybrid

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science or a related field, or equivalent experience may be considered.
• Strong software development skills in Java and Python, with solid knowledge of software design, testing and engineering best practices.
• Strong expertise in AI, with proven experience in building data-driven models and a good understanding of correlation and causal inference techniques.
• Hands-on experience with LLMs and LLM-related tooling (prompt engineering, RAG, embeddings and vector databases, agent and tool-calling frameworks such as LangChain or similar).
• Experience running and fine-tuning AI models locally/on-prem, including GPU/resource requirements and model optimization.
• Proficiency with data/ML libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow).
• Solid DevOps skills: Git, CI/CD pipelines, and automation tools like Jenkins and GitLab/GitHub.
• Good working knowledge of Docker and Kubernetes; familiarity with Prometheus/OpenTelemetry/Loki/Grafana.
• Familiarity with infrastructure as code (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 observability data.
• Develop data-driven ML/AI models, including anomaly detection and time-series analysis.
• Productionize models and services in Java and Python, from prototype to production.
• Design and implement LLM-based applications (RAG, embeddings, tool/calling) for incident analysis and knowledge discovery.
• Deploy AI models on local/on‑prem infrastructure; optimize performance and security.
• Collaborate with DevOps, SRE, and product teams to identify high-value AI opportunities.

Skills

Java

Python

AI / ML

Time series

Causal inference

LLM tooling

Observability concepts

Git

Kubernetes

AWS / GCP

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Docker

Prometheus/OpenTelemetry

Loki

Grafana

Jenkins/GitLab

Terraform

LangChain / similar

Ollama / vLLM / HuggingFace

Job description

Avaloq Philippines Inc. is seeking a Correlation and Causality Engineer to design and implement AI-powered insights from observability data.

You will combine Java/Python development with data-driven models and LLM tooling to detect correlations, infer root causes, and anticipate incidents before they affect clients. You will work across the observability stack (Prometheus, OpenTelemetry, Loki, Grafana) and collaborate with DevOps, SRE, and product teams to deliver scalable AI solutions on hybrid