AWSAzureCloudJavaPythonRubyRuby on RailsC#CAIMachine LearningMLGenerative AILLMOpenAIRAGAgenticAnalyticsRailsBedrockVertex AICI/CDLeadershipProduct Management
About this role
Role Overview
Define and maintain the enterprise AI architecture blueprint and reference models.
Evaluate and select AI platforms, frameworks, vector databases, LLMs, and tooling for application integration.
Provide architectural leadership for generative AI and agentic workflows in products and internal applications.
Establish patterns for retrieval augmented generation (RAG), model orchestration, and evaluation pipelines.
Partner with Data & Analytics to design end to end data flows that support AI workloads, including ingestion, transformation, storage, and retrieval patterns that ensure accuracy and performance.
Ensure AI solutions integrate cleanly with enterprise data ecosystems by defining standards for metadata, lineage, governance, and interoperability across operational systems, data pipelines, and analytical platforms.
Lead end-to-end architecture for AI powered features, including model integration, API design, data flows, and security controls.
Work with development teams to ensure AI components are modular, scalable, and resilient.
Guide teams in fine tuning, prompt engineering, model optimization, and inference best practices.
Oversee architectural reviews and provide hands-on technical support during implementation.
Partner with Security and Compliance teams to ensure AI systems follow responsible AI principles and risk controls.
Define processes for model monitoring, safety evaluations, versioning, data lineage, and auditability.
Ensure adherence to data privacy, intellectual property, and regulatory standards.
Advise the CIO, CTO, and senior leadership on emerging AI technologies and strategic opportunities.
Mentor developers and technical leads to build organizational capability in AI engineering.
Work cross-functionally with product management to translate business needs into AI architectural patterns.
Represent the Application Development team in AI governance and enterprise architecture forums.
Interface and knowledge share with domain experts in Research and Advisory groups.
Requirements
Bachelor’s degree in Computer Science, Engineering, or related field required.
Master’s degree or beyond preferred.
8+years in software engineering or application architecture roles with at least two plus years focused on AI or machine learning.
Hands-on experience with cloud-based AI platforms such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Experience deploying LLM based solutions at scale.
Strong background in APIs, and enterprise application design.
Deep understanding of AI and ML concepts including LLMs, embeddings, vector search, supervised and unsupervised learning, and model lifecycle management.
Proficiency with Python and one or more application development languages such as Ruby on Rails, C#, or Java.
Experience with model orchestration frameworks, prompt engineering, and evaluation techniques.
Familiarity with DevOps practices, CI/CD pipelines, and cloud infrastructure.
Strong understanding of security, privacy, and responsible AI principles.
Tech Stack
AWS
Azure
Cloud
Java
Python
Ruby
Ruby on Rails
Benefits
Opportunity to shape and scale the AI strategy
Work directly with the Founder, CIO, CTO, senior technology leaders, and executive team as required.
Build transformative AI capabilities that enhance products and internal platforms.
Join a collaborative, high-performance Application Development team with a strong innovation mandate.
Collaborate with world-class analysts who cover the AI space.