Senior AI Engineering Lead

Vanigent

Senior AI Engineering Lead responsible for advanced AI solutions at a technology firm. Leading strategy execution, team management, and custom AI developments in Metro Manila, NCR.

Posted 7/29/2026full-timeRemote • 🇵🇭 PhilippinesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying advanced AI solutions, with a strong focus on predictive modeling, MLOps, and cloud AI deployment. Proven leadership in managing AI teams and driving AI strategy aligned with business objectives.

Highest-signal resume keywords

AI Strategy ExecutionPredictive ModelingMLOps / Model Lifecycle ManagementPython ProficiencyCloud AI Deployment

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Software DevelopmentAI / ML EngineeringLLM / Generative AI DevelopmentRAG ArchitectureFine-Tuning TechniquesDatabasesData PipelinesModel ServingMonitoringModel Versioning

Soft Skills

People ManagementTechnical LeadershipCoachingCollaboration

Tools & Technologies

PyTorchTensorFlowScikit-learnHugging Face TransformersLangChainAWSGCPAzureDockerKubernetes

Industry Keywords

Artificial IntelligenceMachine LearningCloud AIMLOpsPredictive Analytics

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaScriptKubernetesNoSQLPythonPyTorchScikit-LearnSQLTensorflowTypeScript

About the role

Key responsibilities & impact

Drive the design, development, and deployment of advanced artificial intelligence solutions
Lead AI strategy execution and guide a team of AI and software developers
Develop custom AI solutions including predictive modeling, RAG systems, and agentic AI workflows
Ensure AI systems are scalable, reliable, and aligned with business requirements
Manage AI and software developers, providing coaching and technical guidance
Partner with product and engineering leaders to identify high-value AI opportunities

Requirements

What you’ll need

5+ years of experience in Software Development
3+ years of experience in AI / ML Engineering in Production
2+ years of experience in LLM / Generative AI Development
2+ years of experience in Cloud AI Deployment
2+ years of experience in MLOps / Model Lifecycle Management
2+ years of People Management / Technical Leadership
Strong proficiency in Python
Working knowledge of TypeScript or JavaScript
Strong experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers
Hands-on experience with RAG architecture, embeddings, semantic search, vector databases, hybrid retrieval, re-ranking, and graph-augmented retrieval
Experience with LangChain, LangGraph, LlamaIndex, OpenAI SDK, Anthropic SDK, and Model Context Protocol or MCP
Experience with vector databases such as Pinecone, Weaviate, pgvector, ChromaDB, or Qdrant
Experience with fine-tuning techniques such as LoRA, QLoRA, RLHF, and DPO
Strong understanding of MLOps, CI/CD, Docker, Kubernetes, model serving, monitoring, and model versioning
Experience with cloud platforms such as AWS, GCP, or Azure
Strong knowledge of databases, data pipelines, SQL, NoSQL, preprocessing, testing, Git, and software engineering best practices.

Benefits

Comp & perks

Paid time off
Flexible work arrangements
Professional development