• Architect, design, and evolve a scalable, secure AI platform and reference architecture that enables rapid development of AI-powered product capabilities
• Drive strategic decision-making across: Model selection and fine-tuning Retrieval-Augmented Generation (RAG) Agent frameworks Data pipelines Inference optimization
• Evaluate and integrate: Open-source and commercial LLMs Vector databases Feature stores MLOps platforms
• Collaborate cross-functionally with Product, Engineering, Architecture, and UX to define AI requirements and priorities
• Lead and influence engineering teams (directly and indirectly), fostering a culture of innovation and architectural excellence
• Lead architecture reviews, technical governance, and long-term platform planning

• Provide architectural direction for Agentic AI systems, including: Workflow orchestration Multi-agent collaboration Context management Safety controls Autonomous decision-making frameworks
• Design and implement LLMOps and AIOps practices for production systems
• Drive observability practices for monitoring agent behavior and system performance
• Define guardrails for: Agent interactions Memory usage Context boundaries

• Define and enforce: Target-state architectures Principles and standards for AI/ML Responsible AI and ethical frameworks (e.g., GDPR, NIST AI RMF)
• Establish processes for metadata extraction and management, enabling granular access control
• Define AI/ML technical capabilities, including: Generative AI systems Data pipelines Model deployment strategies MLOps frameworks
• Develop and maintain AI reference architectures and best practices

• 8+ years of experience as a Senior, Lead, or Principal Engineer/Architect
• Hands-on experience with AI and ML systems in production environments
• Proven ability to lead large-scale architectural initiatives and influence cross-functional decisions

• Strong programming proficiency in: Python (expert-level required) Java, TypeScript, Node.js, or similar
• Experience with AI frameworks such as: LangGraph LangChain LlamaIndex Semantic Kernel AutoGen

• Deep experience with: Large Language Models (LLMs) Embeddings Vector databases RAG architectures Model serving frameworks
• Hands-on experience with Agentic AI patterns, including: Autonomous agents Tool usage Multi-agent coordination Goal-directed planning

• Strong background in cloud platforms: AWS, Azure, or GCP
• Experience with: Containerization Serverless technologies Distributed systems

• Experience designing secure AI systems, including: Data privacy Encryption Compliance Responsible AI practices
• Solid understanding of: API integration patterns Messaging systems Event-driven architectures

• Hands-on experience with: Microservices architectures Domain-driven design (DDD) Platform engineering
• Proven experience building scalable, high-performance distributed systems

• Excellent communication, problem-solving, and technical leadership skills
• Ability to influence and align teams across organizational boundaries

This is an opportunity to work with cutting-edge AI technologies, solve real business challenges, and shape a forward-looking technology strategy.

If you are passionate about AI and ready to tackle complex and impactful challenges, we encourage you to apply.