AI Engineer

Overview 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. This is a remote position. 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 Bachelor’s or Master’s degree in Computer Science, AI, or related domain. At least 5 years experience building production-level LLM, AI agent, or RAG systems. Technical skills: 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. Strong background in MLOps/LLMOps—CI/CD, deployment, monitoring, observability, model versioning, A/B testing. Demonstrated ability to design multi-agent or autonomous systems, with experience in agent orchestration frameworks or custom pipelines. Excellent communication and leadership: ability to translate complex technical ideas and guide teams through innovation. Bonus: prior contributions to open-source, publications in AI, or conference speaking engagements (e.g., on advanced LLM or agent architectures). Work Environment & Expectations While this is a work-from-home position, 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 discipline and commitment to set working hours, use of time tracking software, active participation in team and client calls with camera on, consistent availability, and treating this as a long-term, full-time job. Benefits Monthly Salary: Php 82,000; paid bi-monthly on the 15th and 30th/31st. Overtime and Philippines public holidays compensation. Probation: 6 months; 10 days annual leave credits; 5 days sick leave. HMO after 6-month probation. 13th Month Pay after 30 days; annual salary review. Laptop provided after 30 days; permanent work-from-home with own internet. Shift times: 8:00 AM to 5:00 PM Philippine time, Tuesday to Saturday. Location notes: Baguio City / Muntinlupa City / Manila / Pasig / Taguig, Philippines (remote-friendly). #J-18808-Ljbffr