Acuity Analytics
Linkedin · Posted 2mo ago
Generative AI Engineer
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Indexed description
- Design, build, and deploy AI models, tools, and agents to automate intelligence-heavy workflows in investment research, portfolio management, operations, and client reporting.
- Partner with the Head of Data & AI to define the technical architecture for AI use cases, integrating with Snowflake, Databricks, internal APIs, and event streams in a secure and governed way.
- Implement retrieval augmented generation (RAG) pipelines and prompt conditioning patterns that ground LLMs on Marathon’s proprietary data, documents, and knowledge assets.
- Design and implement Model Context Protocol (MCP)–based integrations so AI assistants and agents can securely discover and connect to internal systems, databases, and services through standardized MCP servers and clients.
- Build and maintain MCP servers that wrap key enterprise services (data warehouses, document stores, workflow systems) and expose tools, resources, and prompts to AI clients in a standardized way.
- Establish patterns for MCP host/client configuration, access control, and observability to ensure reliable, auditable AI interactions with enterprise systems.
- Implement MLOps and LLMOps practices for both model and MCP-based integration lifecycles, including deployment automation, monitoring, logging, and rollback strategies.
- Collaborate with data engineers and platform teams to ensure clean, secure, and well-structured data access for AI consumption, including governance of which systems are exposed via MCP.
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