Lead AI Architect

Company :

enGen

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, Dev Ops, 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 (Sage Maker), Azure (Azure ML), or GCP (Vertex AI). Mastery of the
AI lifecycle
, from frameworks like PyTorch/Tensor Flow 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 of5+ years in software engineering or data science
, with at least3 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…