AI Engineer

Job Description

This is a remote position.

PHILIPPINE-BASED FILIPINO APPLICANTS

TECHNICAL ASSIGNMENT IS REQUIRED BY THE CLIENT BEFORE MOVING FORWARD TO THE FINAL INTERVIEW.

We are seeking a visionary AI Engineer with expertise in designing and building LLM-powered AI pipelines and multi-agent chatbot systems. You will lead the architecture and implementation of Retrieval-Augmented Generation (RAG) systems, integrate LLM APIs, and orchestrate autonomous and collaborative agent workflows to deliver sophisticated AI-driven customer-facing and internal tools.

Responsibilities :

• AI Pipeline Architecture & Development : Design and implement end-to-end AI pipelines, including data ingestion, prompt engineering, RAG orchestration, deployment, monitoring, and retraining.
• Multi-Agent System Design : Build and coordinate intelligent agents (e.g., planner, retriever, synthesizer) to collaborate dynamically in complex workflows—mirroring frameworks like MA-RAG.
• LLM Integration & Fine-Tuning : Deploy and manage integrations with leading LLM APIs (e.g., OpenAI, Anthropic, Gemini), optimizing performance through fine-tuning, prompt design, vector databases, and tool use.
• Tooling & MLOps (LLMOps) : Implement robust MLOps pipelines—CI / CD, monitoring, version control, observability—for LLM systems, supporting reliability and scalability.
• Evaluation & Metrics Frameworks : Define evaluation strategy focused on correctness, latency, hallucination, multi-step reasoning, and user experience—similar to frameworks used in agent pipeline roles.
• Cross-Functional Collaboration & Leadership : Partner with product managers, data engineers, software teams, and domain experts to shape system behavior; mentor junior engineers and guide best practices.

Requirements

○ Python expertise; familiarity with AI / LLM frameworks (LangChain, LlamaIndex, Hugging Face, etc.)

○ Hands-on with RAG, vector embeddings, prompt engineering

○ Experience integrating LLM APIs, fine-tuning strategies, efficient inference, and memory augmentation.

Work Environment & Expectations

While this is a work-from-home position, it is important to note that this is a full-time role—not a freelance or flexible-hour arrangement. You will be expected to work a fixed shift and maintain a high level of professionalism and accountability, just as you would in an office environment.

✅ This role requires :

⏱ Payroll is processed bi-monthly.

We’re looking for someone who values structure, is dependable, and thrives in a role that provides consistency and clarity. If you’re seeking stability and a team that appreciates reliability, we’d love to hear from you.

Benefits

1.  Monthly Salary : Php 82,000

2.   Salary will be paid on a bi-monthly basis on the 15th and 30th or 31st of each month

3.   You will be paid extra for overtime and Philippines public holidays

4.   Probation : 6 months and after Probation

10 days annual leave credits

5 days of sick leave

5. HMO Offered after 6-month probation

6. 13th Month Pay after 30 days

7. Annual Salary Review

8. Laptop provided after 30 days

9. Permanent work-from-home role. You will have to use your own internet.

10. SHIFT TIMES : 8AM to 5PM Philippine time, Tuesday to Saturday

Requirements

A bachelor's or master's degree in Computer Science, Electrical Engineering, or a related field. 5+ years of experience in computer vision, specifically in segmentation techniques. Proficiency in programming languages such as Python and familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch). In-depth knowledge of classical computer vision algorithms (e.g., edge detection, image segmentation). Strong understanding of convolutional neural networks (CNNs) and their applications in image analysis. Experience in training and fine-tuning deep learning models for object detection and segmentation tasks. Familiarity with dental imaging modalities, such as X-ray and intraoral cameras. Excellent problem-solving skills and the ability to work independently or as part of a team. Strong communication skills and the ability to present complex technical concepts to non-technical stakeholders.