Key skills
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.