AI Platform Engineer – Shared AI Capabilities

Landing Point; New York (NY); On-site; USD 114,000 - 162,000; Full time

Job summary

Landing Point, a leading financial services firm in the United States, seeks an AI Platform Engineer to build reusable enterprise AI solutions and move operations from vendor-led to internal teams. You will mature AI foundations, develop RAG pipelines, embeddings services, and memory architectures that support compliant, scalable AI products.

You will implement content ingestion, prompt management, and PII-aware tooling while ensuring robust deployment patterns and telemetry.

Qualifications

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

Responsibilities

• Build and mature shared engineering foundations for AI products.
• Develop RAG and retrieval pipelines as reusable services.
• Create a centralized embeddings service and vector index management.
• Establish a memory bank for persistent, identity-scoped agent memory.
• Design context assembly logic for 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 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.

Skills

RAG

Vector search

Embeddings

Retrieval pipelines

Agent memory

PII handling

Python

AWS

Production services

Job description

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