AI Developer (Metro Manila)

Purpose of the role

You are a forward-thinking, hands-on AI Developer who turns business problems into production-ready AI capabilities, such as building, fine-tuning, and deploying machine learning and Generative AI solutions (including LLMs, RAG, and multimodal models) that are scalable, secure, and measurable.

Responsibilities

Development responsibilities

• Build and maintain AI/ML solutions using Python as the primary language, with Java/C++ where high-performance services are required and R for statistical analysis/prototyping when needed

• Develop, train, evaluate, and optimize models using PyTorch, TensorFlow, and Keras

• Implement classical ML pipelines and experimentation using scikit-learn (feature engineering, model selection, tuning, validation, and performance measurement)

• Build NLP/LLM capabilities using Hugging Face (model selection, fine-tuning, inference optimization, and evaluation)

• Design and deliver RAG and LLM orchestration workflows using LangChain and/or LlamaIndex, including prompt chaining, tool use, routing, and guardrails

• Execute prompt engineering and fine-tuning strategies to improve quality, reliability, and task performance across use cases

• Develop and integrate multimodal AI solutions spanning text, image, audio, and video (as applicable), including data preparation and evaluation

• Design and manage data storage and retrieval patterns across SQL and NoSQL systems, ensuring clean, accessible, well-governed datasets

• Implement semantic search and “AI memory” patterns using vector databases Pinecone, Milvus), including embedding strategies, indexing, and retrieval tuning.

• Deploy, scale, and operate AI workloads on AWS SageMaker, Google Vertex AI, and/or Azure AI, including endpoint management and cost/performance trade-offs

• Establish and follow MLOps best practices: Git-based version control, reproducible experiments, automated testing, CI/CD, model registry, and monitoring for drift/performance

• Debug and improve “black box” behaviour through systematic experimentation, root-cause analysis, and clear documentation of findings and decisions.

• Ensure solutions meet Responsible AI standards: privacy-by-design, secure data handling, bias detection/mitigation, and compliance with relevant legal/ethical requirements

• Collaborate with stakeholders to translate business needs into technical requirements, success metrics, and delivery plans

• Stay current with new research and tooling arXiv, model releases, framework updates) and proactively recommend improvements to the team’s AI approach.

Agency / client communication:

• Maintains regular day-to-day contact with key internal stakeholders to manage their expectations

• Works to ensure clear communication with internal and external contacts through the most appropriate method

• Confident communication, both written and verbal

Team management and leadership:

• Encourages and inspires excellence in both the development and design teams

• Motivates colleagues to work together in the most efficient manner including Project Management and Client Services

• Actively challenges the status quo looking for ways to improve solutions recommended across teams

• Consistently acknowledges and appreciates each team member's contribution

• Records and shares lessons learned with team members to facilitate continuous improvement

Client relationships and new business opportunities:

• Demonstrates an understanding of clients’ businesses and the context of their projects

• Identifies additional opportunities as they relate to a specific project or client

• Continually seeks opportunities to improve delivery against customer requirements

• Be mindful of wider agency and client objectives and work with all areas of the business to deliver against them

About you

• Essential Skillset

  Technical & Programming Skills

  Strong knowledge in Python, Java, C++, and R

  Mastery of PyTorch, TensorFlow, and Keras for model development

  AI Libraries: Scikit-learn (general ML), Hugging Face (NLP/LLMs), LangChain/LlamaIndex (for RAG and LLM orchestration).

  Generative AI Tech: Proficiency in fine-tuning, prompt engineering, and working with multimodal models (Text, Image, Audio, Video).

  Workflow of machine learning for effective data processing outline diagram

  Knowledge in agentic workflow tools, n8n, Zapier, or similar

  Data Engineering & Infrastructure

  Data Management: SQL and NoSQL databases, plus experience with Vector Databases (like Pinecone or Milvus) for AI memory.

  Cloud Platforms: Deployment experience on AWS SageMaker, Google Vertex AI, or Azure AI.

  MLOps: Knowledge of CI/CD for machine learning, version control (Git), and mode

• Confident communication, both written and verbal – occasional client meetings may be required

• A proactive approach and an ability to work independently

• Must have strong communication skills, written and verbal

• A well-rounded understanding of modern web technologies

• Open to shifting hours

• Experience of delivering technically sophisticated/complex creative solutions – demonstrable ability to talk the talk with clients, suppliers, and business stakeholders