Company :

enGen

Job Description :

JOB SUMMARY

We are seeking a visionary AI Architect to serve as the technical cornerstone of our artificial intelligence strategy. While an AI Engineer builds the models, you will design the entire ecosystem they live in. You will be responsible for defining the high-level structure of our AI systems, ensuring they are scalable, secure, and seamlessly integrated with our enterprise infrastructure. As an Architect, you sit at the intersection of business value and technical feasibility, translating executive goals into robust technical blueprints.

This role involves defining the end-to-end architecture for AI solutions, encompassing data pipelines, model storage, inference engines, and front-end integration. The individual will be responsible for evaluating and selecting the optimal "tech stack," including specific LLMs, vector databases, and orchestration frameworks, to meet the company's long-term needs. Key responsibilities also include establishing best practices for MLOps to ensure consistent coding standards, model versioning, and deployment strategies across the engineering team. The architect will design scalable systems capable of handling massive data throughput and low-latency inference for real-time applications. A critical aspect of the role is architecting "Human-in-the-loop" systems and guardrails to ensure data privacy, compliance (GDPR/CCPA), and AI safety. This position requires strong cross-functional leadership, acting as the technical liaison between Data Science, DevOps, and Product teams to align the AI roadmap with infrastructure capabilities.

Candidates should possess architectural expertise, including a deep understanding of distributed systems, microservices architecture, API design, and cloud-native patterns. Proficiency in designing complex data schemas for both structured and unstructured data, as well as experience with Infrastructure as Code (IaC) tools like Terraform or Ansible to manage AI infrastructure, is required. Technical proficiencies include expert-level knowledge of cloud platforms such as AWS (SageMaker), Azure (Azure ML), or GCP (Vertex AI). Mastery of the AI lifecycle, from frameworks like PyTorch/TensorFlow to deployment tools like Kubeflow, MLflow, or BentoML, is essential. An expert understanding of Generative AI, including Transformer architectures, RAG (Retrieval-Augmented Generation), and fine-tuning methodologies, is also a key qualification.

The ideal candidate will have a proven track record of 5+ years in software engineering or data science, with at least 3 years in an architectural role. Experience in enterprise integration, particularly in migrating legacy systems to AI-augmented workflows, is highly valued. This role also demands thought leadership, including the ability to mentor senior engineers and present complex architectural decisions to the C-suite.

Essential competencies for this role include strategic thinking, with the ability to anticipate 12–24 months ahead in AI trends and prepare the infrastructure accordingly. Cost management skills, specifically optimizing cloud spend for GPU/TPU resources, are crucial. Exceptional communication skills are also required, demonstrated through the ability to document architectural patterns and lead technical design reviews.

ESSENTIAL RESPONSIBILITIES

Lead to provide strategic consultation to business customers in defining or designing business processes, functions and organizational structures, as well as in researching, identifying and internally marketing enabling technologies based on customer capability requirements. Facilitate development of the most complex enterprise business solutions that combine knowledge of particular business processes and issues, general technological options, and process facilitation techniques. Lead and participate in enterprise strategy development, including environmental analysis, opportunity identification, value cases and business innovation portfolio development.
Specify and design large or the most complex systems, solutions, networks, infrastructure elements, or processes. Select appropriate design standards, methods and tools and ensures that they are applied effectively. Lead reviews of others’ system design to ensure selection of appropriate technology, efficient use of resources and integration of multiple systems and technology. Establish policy for selection of architecture components. Evaluate and undertake impact analysis on the most complex major design options. Ensure that the system architecture balances functional, service quality and systems management requirements.
Use appropriate tools, including models of components

Lead AI Architect at name