AI Engineer

Full-time · Manila and Cebu

Your Role

Senior AI Engineer working across technology and operations to identify operational pain points, shape loosely defined problems into clear technical plans, and deliver scalable AI/ML solutions that improve team speed and resilience while influencing AI/ML practices across the organization.

Responsibilities

• Design, build, deploy, and maintain production AI/ML systems across predictive analytics, NLP, classification, and generative AI.

• Build practical generative AI solutions with LLMs, RAG, prompt engineering, and model integrations—delivered as production-ready apps and services wired into existing workflows.

• Design and run end-to-end agentic workflows using tool use, memory, orchestration, RAG, and human-in-the-loop patterns.

• Build and maintain MCP servers and integrations that let AI agents work securely with systems, tools, and data.

• Build evaluation harnesses, guardrails, and tests that measure reliability, quality, safety, and operational performance.

• Build and maintain ML pipelines end to end—data prep, feature engineering, training, evaluation, deployment, and monitoring—including drift detection, performance tracking, and automated retraining.

• Own the move from prototype to reliable production, applying the right security, reliability, governance, and operational guardrails, and help raise the team's MLOps standards along the way.

• Find and validate AI/ML opportunities that cut manual effort, improve operational workflows, or sharpen decision-making—translating them into practical solutions and measurable outcomes.

• Communicate technical approaches, trade-offs, and results clearly to both technical peers and non- technical stakeholders.

• Mentor junior engineers and contribute to building the team’s AI/ML practices and standards.

Your Qualifications

• Bachelor's degree in Computer Science, Mathematics, Applied Physics, Data Science, or a related field.

• 3+ years in AI/ML engineering or a closely related technical role.

• Proficiency in Python and the core ML libraries — scikit-learn, PyTorch, TensorFlow, or HuggingFace.

• Hands-on experience building and deploying production AI/ML systems across the full lifecycle: data prep, model selection, development, evaluation, deployment, monitoring, and maintenance.

• Experience with commercial AI platforms — Claude (Anthropic), AWS Bedrock, AWS SageMaker, or the Azure AI equivalents.

• Practical experience with generative AI: LLMs, RAG, prompt engineering, and getting AI applications into production.

• A working command of responsible AI — security, privacy, evaluation, safety, governance, and the right guardrails.

• Experience with PostgreSQL, Apache Spark, Apache Iceberg, or comparable data platforms.

• Experience in building and maintaining MCP servers.

• Comfortable guiding and mentoring junior team members — reviewing their work, unblocking them, and helping them level up.

Nice to Have
We don't require expertise in every area below—but prior exposure helps.

• Implementing AI evaluation harnesses, observability, automated testing, and production guardrails.

• Working with agentic AI — the underlying concepts and end-to-end agent workflow design.

• Designing full AI architectures: APIs, RAG systems, multi-model workflows, and production deployment.

• Experience with LangChain and/or LangGraph.

Ready to start your awesome journey and be part of OpsWerks?