Sr. AI Developer
Taguig City, Ncr-Fourth District
Build LLM modules for RCA, Incident Summaries, correlation logic, and remediation workflows using operational data sources such as SOPs, ELK logs, and ServiceNow tickets. Develop machine learning models to detect anomalies in system and infrastructure logs.Integrate AI solutions with existing platforms to enhance monitoring, reporting, and automation capabilities.Ensure that AI models follow responsible AI practices, governance requirements, and documentation standards. Collaborate with cross functional teams to refine AI requirements, support testing, and improve model outputs.
Qualifications
Bachelor's degree in IT, Computer Science or any IT related field.Practical experience in developing and deploying AI systems Hands-on experience designing transformer based workflows, dynamic prompts, andLLM driven automation for operational use cases such as incident analysis and RCA.Experience building tokenization pipelines, embeddings, prompt engineering, and fine tuning using frameworks such as Hugging Face, LangChain, and OpenAI libraries. Experience deploying and configuring vector databases for semantic search, including HNSW indexing, metadata filtering, and sharding using platforms such as Milvus, Pinecone, or Azure AI Search. Experience implementing Retrieval Augmented Generation pipelines with chunking strategies such as semantic chunking, sliding window, or hierarchical chunking. Experience integrating LLM workflows with enterprise systems such as ELK Stack, SOP repositories, and ServiceNow tickets. Experience with ML model lifecycle management including training, evaluation, deployment, and performance monitoring.
Must Have
Bachelor's degree in IT, Computer Science or any IT related field.Practical experience in developing and deploying AI systemsHands-on experience designing transformer based workflows, dynamic prompts, and LLM driven automation for operational use cases such as incident analysis and RCA.Experience building tokenization pipelines, embeddings, prompt engineering, and fine tuning using frameworks such as Hugging Face, LangChain, and OpenAI libraries.Experience deploying and configuring vector databases for semantic search, including HNSW indexing, metadata filtering, and sharding using platforms such as Milvus, Pinecone, or Azure AI Search.Experience implementing Retrieval Augmented Generation pipelines with chunking strategies such as semantic chunking, sliding window, or hierarchical chunking.Experience integrating LLM workflows with enterprise systems such as ELK Stack, SOP repositories, and ServiceNow tickets.Experience with ML model lifecycle management including training, evaluation, deployment, and performance monitoring.