Titan is building the AI platform for banking, led by a team of former CTOs with multiple exits. We are creating secure, bank-native AI infrastructure and applications that meet the needs of modern banking and financial services. Our platform includes: Titan Foundry (secure gateway to top AI models for bank employees), Banking-Reasoning Models (flagship small language models purpose-built for financial services), and Banking Agents (configurable AI application layer). Our team comprises former founders, CTOs, engineers, operators, and regulators from prominent institutions.

About the Position

Introduction

Titan is building the AI platform for banking, focused on creating models and agents that will define the industry. We are looking for an AI LLM Retrieval Engineer to join our team to build the data and retrieval backbone for autonomous banking and fintech.

Responsibilities

Architect and maintain client-specific and internal RAG pipelines, including embedding generation, document chunking, and metadata tagging.
Collaborate directly with enterprise clients to assess data landscapes, retrieval requirements, and grounding needs.
Select, test, and optimize embedding models (text, multimodal) for accuracy and efficiency.
Design retrieval strategies (dense, sparse, hybrid) to maximize precision and recall.
Establish and monitor evaluation metrics for retrieval performance (e.g., recall@k, MRR, nDCG).
Align retrieval structure, granularity, and metadata with reasoning workflows.
Maintain documentation, schemas, and retrieval guidelines for internal and client teams.
Stay current with advancements in vector databases, embedding models, and retrieval frameworks.

Requirements

Proven track record building and optimizing retrieval systems in production.
Deep understanding of embedding models, indexing strategies, and ANN search.
Experience with vector DBs (e.g., Pinecone, Weaviate, Milvus, Vespa, FAISS).
Strong proficiency in Python and familiarity with RAG frameworks (LangChain, LlamaIndex, Haystack).
Knowledge of relevance tuning, hybrid search, and retrieval evaluation.
Experience working with graph databases (Neo4J, ArangoDB).
Strong communication skills for technical and client-facing collaboration.

Benefits

Competitive compensation (salary + meaningful, pre-Series A equity).
Remote-first culture with opportunity for in-person collaboration.
Unlimited PTO.
Medical, dental, and vision coverage (100% of employee premiums paid by Titan).

About Company

Titan Foundry: Secure gateway to top AI models for bank employees.
Banking-Reasoning Models: Our flagship small language models purpose-built for financial services, trained by ex-regulators and banking leaders.
Banking Agents: Configurable AI application layer with expertise in lending, compliance, underwriting, and operations. Our small team consists of former founders, CTOs, engineers, operators, and regulators from places like Goldman Sachs, KeyBank, and the Office of the Comptroller of the Currency. We have built and sold companies to top 25 U.S. banks. If you’re a high-agency individual who loves tackling complex problems in an emerging space, we want to hear from you!