AI Architect

We are seeking an experienced AI Architect to lead the end-to-end design and implementation of enterprise Generative AI platforms. This role involves overseeing all aspects of architecture, including data management, retrieval systems, multi-agent frameworks, integration, security, and deployment. The ideal candidate will have a strong background in designing complex AI systems and a deep understanding of the trade-offs involved in model selection, vector stores, and operational frameworks. You will collaborate closely with telecom and enterprise clients, guiding technical teams and ensuring high standards in AI operations and security.

Key Responsibilities

- Own the complete architecture for enterprise Generative AI platforms, covering data ingestion, retrieval mechanisms, agent frameworks, integration points, security protocols, and deployment strategies.
- Design Retrieval-Augmented Generation (RAG) systems, including data ingestion, chunking methods, embedding strategies, vector store selection, and hybrid retrieval techniques.
- Develop multi-agent systems with roles such as supervisor/worker and planner/executor, managing routing, shared state, memory, and deterministic fallback mechanisms.
- Define the integration architecture for Multi-Cloud Platforms (MCP), including server infrastructure, tooling, schema design, authentication processes, scoped permissions, and auditing capabilities.
- Evaluate and select appropriate models, vector stores, and frameworks by balancing quality, cost efficiency, data residency requirements, and portability.
- Implement robust security designs addressing threat models, prompt-injection defenses, least-privilege access controls, and permission-aware retrieval systems.
- Establish standards for Large Language Model Operations (LLMOps), including evaluation protocols, change control processes for models, prompts, and agents.
- Lead customer workshops and design review sessions, producing comprehensive architecture deliverables tailored to telecom and enterprise clients.
- Mentor and guide engineering teams through design discussions and code reviews, fostering best practices and technical excellence.

Required Qualifications

- Proven experience in architecting and delivering enterprise-scale Generative AI platforms.
- Strong expertise in designing RAG systems, multi-agent AI frameworks, and integration architectures.
- Deep understanding of vector stores, embedding techniques, and hybrid retrieval methods.
- Solid knowledge of security principles relevant to AI systems, including threat modeling and access control.
- Experience with LLMOps, including model evaluation, prompt engineering, and operational change management.
- Ability to lead technical workshops and communicate complex architectural concepts effectively to clients and internal teams.
- Demonstrated leadership skills in mentoring engineers and conducting thorough design and code reviews.

Preferred Qualifications and Benefits

- Experience working with telecom or large enterprise clients is highly desirable.
- Familiarity with multi-cloud environments and MCP integration is a plus.
- Strong analytical skills with the ability to balance trade-offs in model and infrastructure selection.
- Opportunity to work on cutting-edge AI technologies in a collaborative and innovative environment.
- Engage with diverse teams and clients, contributing to impactful AI solutions at scale.

This position offers the chance to shape the future of enterprise AI platforms by driving architectural excellence and operational rigor. If you are passionate about AI innovation and enjoy leading complex technical initiatives, we encourage you to apply.