Titan Decorative Materials Group

AI Engineer

• Act as the global lead and subject matter expert for AI-related initiatives, including GenAI, across TITAN Group
• Design the overall AI orchestration architecture and blueprints for AI platforms and their integration with the Group’s IT and digital technology stack
• Design AI pipelines, including RAG architectures, LLM orchestration layers, agent workflows, and evaluation frameworks
• Translate business and regulatory requirements into secure, scalable, production-grade technical blueprints
• Define reference architectures, reusable patterns, and engineering standards for AI adoption at scale
• Evaluate vendors and platforms
• Write production-quality Python and related frameworks
• Integrate and validate MVPs, PoCs, and acquired AI solutions
• Implement agentic AI systems, including tool use, multi-agent orchestration, MCPs, memory management, and autonomous decision workflows
• Deploy and integrate AI components into enterprise applications, APIs, data platforms, and third-party systems
• Design observability stacks for prompt monitoring, model response tracking, vector retrieval quality, and agent execution workflows
• Manage model lifecycles, including versioning, drift detection, evaluation-driven development, retraining pipelines, bias, fairness, and transparency
• Optimize inference cost, latency, and throughput at scale
• Establish and enforce AI governance frameworks covering auditability, data privacy, and model risk management
• Ensure compliance with enterprise security standards, including IAM, encryption, and regulatory requirements
• Develop tools and methodologies to monitor and optimize AI usage costs in collaboration with FinOps
• Drive responsible AI practices across multi-team and multi-vendor environments
• Advise senior leadership and business units on technical matters
• Mentor engineers and architects and foster engineering excellence
• Lead knowledge-sharing, community-building, and internal AI enablement initiatives
• Stay current with the AI landscape and introduce tools, frameworks, and patterns to improve team capability

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