AI Engineer

D2B; Metro Manila; On-site; PHP 804,000 - 1,339,000; Full time

Job summary

D2B in the Philippines is seeking an AI Engineer to design and deploy production-grade AI and ML solutions for enterprise clients. You will turn client problems into scalable systems that clients can operate after engagement ends, working with Australian clients across retail and energy sectors.

Responsibilities cover architecture, LLM integration, data pipelines and production monitoring. The role requires 5+ years software engineering with AI production experience, consulting experience, and

Qualifications

• 5+ years of professional software engineering, including at least two years building AI applications in production.
• Consulting or professional services experience delivering to external clients against 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 maintainable code.
• Daily use of AI engineering tools such as Claude Code or Codex.
• Hands-on experience integrating LLMs into applications (RAG, prompt design, tool use, evaluation).
• Experience building agents with MCP or agent frameworks.
• Experience training and deploying ML models with libraries like scikit-learn, PyTorch or XGBoost.
• Strong SQL and building data pipelines.
• Experience deploying solutions on cloud platforms (Azure/AWS) with containers/CI/CD.
• Ability to explain technical trade-offs to non-technical execs in plain language.

Responsibilities

• Design the solution architecture, selecting models (off-the-shelf, RAG, agents, or custom) per client problem and budget.
• Integrate LLMs into client systems with prompts, tools and agent workflows.
• Train, validate and deploy ML models for forecasting and anomaly detection.
• Analyze client data to test feasibility and build data pipelines powering models.
• Evaluate and monitor production solutions for accuracy, drift, latency and cost.
• Write tested, secure code with guardrails against prompt injection and data leakage.
• Collaborate with client executives, business users and IT teams to translate business needs into technical requirements.
• Handover solutions with documentation and training so client teams can run them.

Skills

Advanced Python

LLM integration

Data pipelines

Cloud platforms" Azure/AWS

SQL

Model deployment

Agent frameworks

Consulting delivery

Executive communication

Education

Bachelor's or Master's in CS/Engineering/Math/Physics

Tools

Claude Code

Codex

scikit-learn

PyTorch

XGBoost

Job description

Position : AI Engineer

Salary : Up to PHP 120,000/month

Working Hours & Conditions: Observing AU working hours

Holidays : Observing AU holidays

A boutique consulting firm is looking for an AI engineer to build and deploy production-grade AI and machine learning solutions for enterprise clients. You will turn a client's business problem into a system that fits their needs and that their team can run and maintain after the engagement ends. Clients are listed and privately owned Australian businesses in retail, consumer goods, energy and mining. The work covers LLM applications and classical machine learning, and it includes the data pipelines underneath both. You will work directly with the founder and with client teams, across scoping through to go-live and handover.

RESPONSIBILITIES:

• Design the solution architecture, choosing between off-the-shelf models, RAG, agents and custom models based on the client's problem and budget.
• Integrate LLMs into client systems, including prompt design, tool use and agentic workflows.
• Train, validate and deploy machine learning models for problems such as demand forecasting and anomaly detection.
• Analyse client data to test whether a use case is feasible, and build the data pipelines that feed models and applications.
• Evaluate and monitor solutions in production for accuracy, drift, latency and cost, and optimise them as issues appear.
• Write tested, secure code, with guardrails against prompt injection and data leakage.
• Work with client executives, business users and IT teams to turn business problems into technical requirements and give input into the firm's proposals.
• Hand over solutions with documentation and training so that client teams can run them

• 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.
• Experience with LLM evaluation and observability tools, such as MLflow, Langfuse or LangSmith.
• Knowledge of LLM security risks, such as those in the OWASP Top 10 for LLM Applications.
• Experience running training sessions or workshops for technical or business audiences.