AI Platform Engineer – Shared AI Capabilities

Company Overview: A leading financial services company is seeking an AI Platform Engineer to enhance its AI capabilities. This role focuses on building reusable enterprise AI solutions, transitioning from vendor-led to internal team operations.

Job Responsibilities:

• Build and mature shared engineering foundations for AI products.
• Develop Retrieval-Augmented Generation (RAG) and retrieval pipelines as reusable services.
• Create a centralized embeddings service and vector index management.
• Establish a memory bank capability for persistent, identity-scoped agent/assistant memory.
• Design context assembly logic for consistent, reusable prompts.
• Implement content ingestion and processing pipelines for enterprise knowledge sources.
• Develop prompt and configuration management systems for versioning and reuse.
• Create a shared PII detection and redaction library.
• Build a platform SDK and golden-path templates for compliant AI product deployment.
• Integrate evaluation hooks for quality checks in AI products.
• Implement telemetry integration for usage, performance, and quality signals.
• Align identity and access integration with enterprise standards.
• Standardize deployment patterns and support practices for AI products.

Qualifications:

• 7+ years of experience in software or platform engineering, with recent work in AI/ML or data-intensive systems.
• Practical experience with RAG, vector search, embeddings, and retrieval pipeline design.
• Familiarity with agent memory, context management, and PII-handling patterns.
• Strong software engineering fundamentals: APIs, testing, CI/CD, and observability.
• Experience with prompt/configuration management and integrating LLMs into production systems.
• Proficiency in Python and/or another primary backend language.
• Fluent in AWS, with familiarity with other major cloud platforms (Azure, GCP).
• Experience operating and supporting production services.

Compensation: Pay Rate: $100 – $100/hr, DOE

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