Overview
We are seeking a highly experienced AI Lead / Architect to support evolving AI initiatives. This
role will work closely with Product, Engineering, and Data teams to define, shape, and deliver
practical AI-driven solutions across the organization.
This is a hands-on leadership role, requiring both strategic oversight and the ability to
contribute directly to solution design and implementation.
Key Responsibilities
Partner with Product and Engineering leadership to identify and prioritize high-impact
AI/GenAI use cases
Define solution architectures for AI-driven capabilities across data, applications, and
workflows
Provide hands-on technical leadership (~30–40%) in areas such as prototyping, model
integration, and solution validation
Guide teams on best practices for leveraging AI/GenAI tools within existing
development workflows
Support the development of scalable, reusable AI patterns and accelerators
Collaborate with data teams to ensure strong alignment on data readiness, governance,
and model performance
Help establish practical frameworks for evaluating and deploying AI use cases in a
controlled and scalable manner
Required Experience
10–15+ years of experience in software engineering, data engineering, or related
technical roles
5+ years of experience working with AI/ML systems, including recent exposure to
GenAI/LLMs
Proven experience designing and implementing AI-driven solutions in enterprise
environments
Strong understanding of:
o LLMs and GenAI ecosystems
o Model integration and APIs (e.g., OpenAI, Azure OpenAI, etc.)
o Data pipelines and data architecture
Experience working cross-functionally with Product and Engineering teams
Ability to balance strategic thinking with hands-on execution
Preferred Qualifications
Experience working in regulated or data-sensitive environments
Familiarity with tools/platforms such as Azure AI, Databricks, or similar ecosystems
Prior experience helping organizations adopt AI in a structured, scalable way
Strong communication skills and ability to influence senior stakeholders
Key Attributes
Pragmatic and execution-focused
Comfortable operating in fast-paced, evolving environments
Strong collaborator with a “build with the team” mindset
Able to translate complex AI concepts into practical business value