AI Engineer

Pear Tree.

. Design solution architecture using off-the-shelf models, RAG, agents and custom models based on client problems and budgets.

Posted 10/15/2026full-timeRemote • PhilippinesMid-LevelSenior💰 ₱120,000 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and integrating AI solutions, including LLMs and machine learning models, while effectively communicating technical requirements to non-technical stakeholders. Proficient in building and optimizing data pipelines and production solutions across cloud platforms.

Highest-signal resume keywords

Advanced Python ProgrammingLLM Integration and Prompt DesignMachine Learning Model Training and DeploymentData Pipeline Development with SQLCloud Deployment on Azure or AWS

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisSoftware EngineeringModel Context Protocol (MCP)Testing and PackagingAnomaly DetectionDemand ForecastingCI/CDContainersSQL

Soft Skills

Client CommunicationTechnical DocumentationTraining and Handover

Tools & Technologies

Claude CodeCodexScikit-learnPyTorchXGBoostDatabricksSnowflakeMicrosoft FabricDbtMLflow

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in EngineeringMaster's Degree in MathematicsMaster's Degree in Physics

Industry Keywords

AI ApplicationsConsultingProfessional ServicesData PipelinesLLM Security Risks

Tech Stack

Tools & technologies

AWSAzureCloudPythonPyTorchScikit-LearnSQL

About the role

Key responsibilities & impact

Design solution architecture using off-the-shelf models, RAG, agents and custom models based on client problems and budgets.
Integrate LLMs into client systems, including prompt design, tool use and agentic workflows.
Train, validate and deploy machine learning models for demand forecasting, anomaly detection and similar problems.
Analyse client data to assess use-case feasibility and build supporting data pipelines.
Evaluate and monitor production solutions for accuracy, drift, latency and cost, and optimise them.
Write tested, secure code with safeguards against prompt injection and data leakage.
Work with client executives, business users and IT teams to translate business problems into technical requirements and contribute to proposals.
Hand over solutions with documentation and training so client teams can operate and maintain them.
Work directly with the founder and client teams from scoping through go-live and handover.

Requirements

What you’ll need

5+ years of professional software engineering, including at least two years building AI applications that run in production.
Consulting or professional services experience, delivering to external clients against a fixed scope.
A bachelor's or master's degree in computer science, engineering, mathematics or physics, or equivalent practical experience.
Advanced Python, including testing, packaging and writing code that other engineers can maintain.
Daily use of AI engineering tools such as Claude Code or Codex, including reviewing, testing and correcting the code they generate.
Hands-on experience integrating LLMs into applications, including RAG, prompt design, tool use and evaluation.
Experience building agents with the Model Context Protocol (MCP) or agent frameworks.
Experience training and deploying machine learning models with libraries such as scikit-learn, PyTorch or XGBoost.
Strong SQL and experience building data pipelines.
Experience deploying solutions on at least one cloud platform, preferably Azure or AWS, using containers and CI/CD.
The ability to explain technical trade-offs to non-technical executives in plain language.
Desired (not required): Experience with data platforms such as Databricks, Snowflake or Microsoft Fabric, and transformation tools such as dbt.
Desired (not required): Experience with LLM evaluation and observability tools, such as MLflow, Langfuse or LangSmith.
Desired (not required): Knowledge of LLM security risks, such as those in the OWASP Top 10 for LLM Applications.
Desired (not required): Experience running training sessions or workshops for technical or business audiences.

Benefits

Comp & perks

Observing AU working hours
Observing AU holidays