Note: Fidelity will not provide immigration sponsorship for this position.

AltIQ is seeking an Applied AI / ML Engineerto help build the intelligence layer of our alternative investment platform.

This role will focus on redefining complex financial documents and datasets into structured, searchable, and actionable information. You will build and implement solutions that parse documents, generate embeddings, drive similarity-based search, and enable retrieval of information across a large corpus of investment-related content, including private placement memoranda (PPMs), prospectuses, deal registration documents, performance reports, investor presentations, and other alternative investment materials.

Collaborating directly with Data Engineering and Product teams, you will help build scalable AI-powered capabilities. These capabilities enable advanced search, document intelligence, knowledge retrieval, and analytics across both structured and unstructured datasets.

This is a hands-on engineering role for someone who enjoys building production-grade AI systems and applying modern machine learning techniques to tackle real business problems.

• Build and develop document parsing and information extraction solutions for intricate financial paperwork.
• Build and maintain embedding pipelines that convert unstructured content into searchable knowledge assets.
• Design, develop, and optimize semantic search and vector retrieval capabilities.
• Develop Retrieval-Augmented Generation (RAG) solutions that combine large language models with proprietary investment data.
• Work in close coordination with Data Engineers to integrate AI workflows into enterprise-scale data pipelines.
• Build APIs and services that expose AI-powered capabilities to internal and external applications.
• Develop and maintain user documentation, architecture diagrams, and operational procedures.
• Collaborate with Product and Business teams to translate user needs into intelligent platform capabilities.
• Provide technical recommendations regarding AI architecture, model selection, and infrastructure requirements.
• Mentor junior engineers and contribute to engineering guidelines.

• Experience with Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, or similar technologies.
• Experience with LangChain, LlamaIndex, Hugging Face, or related AI frameworks.
• Experience building enterprise search, knowledge management, or document intelligence platforms.
• Experience with OCR and document processing technologies.
• Knowledge of MLOps and machine learning deployment patterns.
• Experience working with financial services, investment data, or alternative investments.
• Familiarity with private equity, venture capital, private credit, hedge funds, or real estate investment products.