About the role
Key
Responsibilities 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 Agentic AI & Advanced Systems 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 Governance & Standards 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
Qualifications Experience 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 Technical Skills 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 AI / ML Expertise 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 Architecture & Platforms Strong background in cloud platforms: AWS, Azure, or GCP Experience with: Containerization Serverless technologies Distributed systems Security & Systems Design Experience designing secure AI systems, including: Data privacy Encryption Compliance Responsible AI practices Solid understanding of: API integration patterns Messaging systems Event-driven architectures Modern Architecture Hands-on experience with: Microservices architectures Domain-driven design (DDD) Platform engineering Proven experience building scalable, high-performance distributed systems Leadership & Communication Excellent communication, problem-solving, and technical leadership skills Ability to influence and align teams across organizational boundaries
