Senior Lead AI Engineer

The Senior Lead AI Engineer is a squad leader responsible for mentoring their squad members and ensuring conformance to GCS AI Engineering technical architecture, governance and processes . This role drives innovation across their Squad’s AI Use Cases, whilst ensuring alignment with enterprise strategy, and acts as an authority on AI systems and agentic platforms.
Duties & Accountabilities
Lead design of complex, large-scale, multi-agent systems
Influence engineering standards, governance models, and development frameworks
Act as technical expert across AI Engineering initiatives
Drive innovation through evaluation of emerging technologies and approaches
Influence technical direction across multiple teams and portfolios
Mentor AI engineers within their Squad
Ensure alignment with responsible AI principles, security, and compliance
Scope & Impact
Operates at portfolio level
Shapes technical direction across multiple initiatives within their Squad
Influences strategic decisions on AI architecture
Impact is enterprise-level within GCS AI Engineering
Acts as a key bridge between strategy and execution
Competencies & Skills
Expertise in enterprise AI architecture and distributed systems
Deep understanding of AI platforms, LLM ecosystems, and agentic systems
Strong strategic thinking and systems mindset
Proven ability to lead complex technical programmes
Strong influence across engineering and product leadership
Essential
Bachelor's degree in computer science, Software Engineering, Data Science, Mathematics, Statistics, or related technical field. Masters will be an added advantage
Equivalent practical experience with software engineering and AI/ML
For Senior Lead 8–10+ years in software engineering.
Evidence of curiosity and continuous learning, with practical AI/ML or LLM application experience.
Understanding of data handling and AI model behaviour
Value Additions:
Prior exposure to enterprise SaaS platforms and large-scale AI/ML deployments.
Familiarity with IFS industries and domain product offerings.
Experience with executive-level customer engagement.
Demonstrated hands-on experience with CI/CD pipelines, utilizing tools such as Bitbucket Pipelines, Azure DevOps, GitHub Actions, or Jenkins.
Proficiency in Infrastructure-as-Code (IaC) tools, including Terraform or Bicep.
Familiarity with test automation practices and tools as part of the CI/CD process.
Comprehensive working knowledge of Microsoft Azure, encompassing compute, storage, networking, and cost optimization.

Employment type
Full-time

Work arrangement
Hybrid