Senior AI Engineer

Schedule: Monday to Friday (6:00AM - 3:00PM PHT)

Contract: 6 months

What are we looking for?

The Senior AI Engineers will play a key role in advancing our AI adoption program—building production-ready prototypes, integrating AI into business workflows, and enabling teams across Marketing, Sales, Finance, Legal, and Operations to leverage AI effectively.

Skills Required:

• 2+ years' professional experience in AI/ML engineering or applied data science
• Strong knowledge of LLMs, generative AI, and AI platforms (e.g., ChatGPT, Claude, Gemini, Copilot, Dataiku, Workato, etc.)
• Proven ability to design, develop, and deploy AI solutions in real-world business environments
• Familiarity with Python, APIs, and cloud environments (AWS, Azure, or GCP)
• Strong problem-solving skills and ability to quickly prototype and iterate
• Effective communication skills to translate technical solutions for business stakeholders

What will you do?

Core Technical Capabilities

• Solution prototyping: They can prove out ideas quickly through the fast creation of proof-of-concepts. They choose the simplest and most appropriate solution without being biased by the latest trends, because speed to insight is crucial.
• Prompt engineering expertise: They are proficient in prompt and context engineering, starting with simple prompts and evolving them through complexity levels.
• Agentic AI and agent protocols: They design and implement autonomous AI agents that can plan, execute, and adapt across multi-step workflows.
• Validation and evaluation skills: They create robust evaluation frameworks to assess GenAI solution performance. They understand LLM monitoring, develop appropriate metrics, and integrate evaluation processes into the development lifecycle. "It seems to work" is not sufficient for production.
• RAG architecture and data integration skills: They build and deploy RAG architectures with advanced data handling, constructing complete data pipelines for retrieval-augmented generation. This includes extracting text from structured and unstructured sources like PDFs and using advanced techniques such as reranking, self-RAG, and HyDE.
• Software development best practices and testing: They implement CI/CD pipelines, test-first development, automated testing, and modular architectures. Production readiness isn't optional.
• Cloud platforms, AI security and ethics: They leverage cloud AI offerings and understand the security implications of GenAI solutions. This includes creating mitigation strategies like LLM red teaming and advocating for responsible AI usage, considering bias, fairness, and societal impact.

LLM Knowledge and Model Management

• Model selection and cost optimisation: They evaluate trade-offs between open-source versus proprietary models and understand their cost implications. They are conscious that every API call and test costs money and design accordingly.
• LLM integration architecture: They design robust APIs with proper error handling and scalable integration architectures. They understand token management and streaming responses for enterprise-grade integrations.

Communication and Collaboration

• Technical communication and collaboration: They translate technical concepts into business value and manage expectations with product managers and business stakeholders.
• Data storytelling and business impact communication: They create compelling narratives that connect GenAI solutions to business impact. They use data visualisation and concrete examples to make the benefits of AI tangible for decision-makers.

JOIN CONNECTOS NOWConnectOS is certified as a Great Place to Work and is a top-rated Philippines employer of choice.

Equal Employment StatementEmployment decisions at ConnectOS will be conducted without consideration of factors such as age', race, color, religion, gender, disability status, sexual orientation, gender identity or expression, genetic information, and marital status. ConnectOS ensures the full confidentiality of the data it processes.