Artificial Intelligence Engineer

Responsibilities:

· Design end-to-end architecture for AI agents.

· Define integration points with authentication, entitlements, and existing systems.

· Oversee implementation of centralized Vector Store and ingestion pipeline.

· Ensure compliance with security and regulatory standards.

· Implement embedding generation and vector similarity search.

· Optimize models for performance (response time 90%).

· Collaborate on explainability and compliance features.

· Build ingestion pipeline for structured/unstructured content.

· Implement scalable Vector Store with metadata and entitlement-aware retrieval.

· Integrate with content platforms (AEM, SharePoint, Content Cloud).

· Ensure audit logging and encryption standards.

· Develop automated and manual test plans for AI agents and content retrieval.

Skills:

· Expertise in AI/ML architecture and enterprise integration.

· Strong knowledge of RAG (Retrieval-Augmented Generation) frameworks.

· Familiarity with IAM, RBAC, and financial services compliance.

· Experience with cloud platforms (AWS, Azure) and containerization.

· Proficiency in Python, TensorFlow/PyTorch.

· Experience with OpenAI/Cohere APIs and local embedding models.

· Knowledge of NLP, semantic search, and multi-turn conversation design.

· Familiarity with CI/CD for ML pipelines.

· Strong backend development (Java, Python, ).

· Experience with vector databases (OpenSearch, Pinecone, Weaviate).

· API development and integration with enterprise systems.

· Knowledge of data security and compliance frameworks.

· Expertise in SQL, data modeling, and ETL tools.

· Familiarity with AWS Textract or OCR services.

· Experience with financial data schemas and governance.