Senior AI Solutions Engineer - Production ML & Dashboards

Poet Technologies Pte Ltd

Santo Niño 1st

On-site

PHP 1,500,000 - 2,100,000

Full time

11 days ago

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Job summary

Poet Technologies Pte Ltd in the Philippines is seeking a Senior Engineer, AI Solutions to deliver production-ready AI systems for manufacturing and business teams. You will own the end-to-end lifecycle from requirements and model selection to deployment and continuous improvement.

You will build dashboards and applications for real-time shipment, test outputs, and supply chain visibility, and you will design auditable AI workflows with human review and fallback mechanisms to ensure

Qualifications

4+ years of professional experience delivering software or data solutions into production with end-to-end ownership.
Strong Python and SQL skills, with experience building dashboards or web applications using FastAPI, Streamlit, Plotly Dash, Grafana, or Metabase.
Applied ML experience in data science/statistics, computer vision, or LLM applications, including model selection, evaluation, and fine-tuning.
Hands-on LLM experience, including tool use, retrieval, agentic workflows, and model-output evaluation.
Daily use of AI-assisted development tools such as Claude Code, Codex, or Cursor, with production software successfully shipped using these tools; Bachelor's/Master's degree in a relevant technical field.

Responsibilities

Drive end-to-end delivery of AI solutions, from user requirements through production deployment and adoption.
Build dashboards and applications for live shipment and test output, real-time tester and equipment monitoring with alerting, and supply chain visibility.
Develop statistical and ML solutions to identify and prioritize yield, test, cost, and operational improvement opportunities.
Select, evaluate, and fine-tune ML/LLM models based on available data, business impact, and cost of errors.
Build agentic workflows and evaluation frameworks for reporting, data consolidation, natural-language querying, and document processing.
Design human-review and fallback mechanisms for AI-driven decisions, keeping critical workflows deterministic and auditable.
Monitor, evaluate, and continuously improve deployed AI solutions with measurable business outcomes.