We are looking for a highly skilled Applied AI Engineer to support the development of an enterprise Generative AI platform within Fixed Income Institutional Lending.

You will build production-grade AI capabilities across document intelligence, enterprise search, embedded assistants, and automated business workflows. This is a hands-on engineering role focused on building and operating GenAI solutions in complex enterprise environments.

About You:

You are a senior engineer with strong software engineering and system design fundamentals and deep experience across RAG, retrieval, document intelligence, and agentic AI.

You understand AI systems under the hood and can explain your architecture, technical decisions, trade-offs, evaluation methods, and production challenges. You are comfortable building AI capabilities from the ground up where security, reliability, governance, and scalability matter.

As a Strategio Applied AI Engineer you will:

• Design and build production-grade GenAI applications and reusable AI workflows.
• Architect advanced RAG and retrieval systems using embeddings, vector databases, chunking, semantic/hybrid search, metadata filtering, and re-ranking.
• Build AI-powered document ingestion and extraction pipelines with validation, traceability, and human-in-the-loop review.
• Develop agentic workflows and AI assistants using tool/function calling, structured outputs, orchestration frameworks, and enterprise data.
• Make architecture decisions across models, retrieval, APIs, orchestration, scalability, latency, and performance.
• Establish LLMOps and evaluation practices across testing, observability, monitoring, version management, and feedback loops.
• Troubleshoot production issues involving hallucinations, retrieval/model regressions, data quality, latency, and reliability.
• Engineer solutions that meet enterprise security, PII, governance, entitlement, and auditability requirements.

Core Skills

• 5+ years of software engineering experience with strong hands-on development skills in Python or Java.
• 2+ years of dedicated GenAI experience building and operating solutions in production enterprise environments.
• Deep hands-on experience with RAG and retrieval architecture, including embeddings, vector databases, chunking, semantic/hybrid search, metadata filtering, and re-ranking.
• Experience with advanced retrieval techniques including multi-stage/multi-vector retrieval, ColBERT or similar late-interaction approaches, and retrieval evaluation.
• Strong software architecture and system design skills with the ability to explain technical decisions and trade-offs.
• Hands-on experience with agentic workflows, tool/function calling, structured outputs, and GenAI orchestration frameworks.
• Strong LLMOps experience including evaluation, regression testing, observability, monitoring, and prompt/version management.
• Experience building AI document ingestion/extraction pipelines and troubleshooting production AI systems.
• Experience building AI capabilities from the ground up, beyond primarily consuming third-party APIs or prebuilt solutions.

Nice-to-Haves:

• Financial services, Fixed Income, Institutional Lending, or regulated enterprise experience.
• AI experience across document intelligence, enterprise search, contracts/credit agreements, reconciliation, or natural-language-to-data.
• Knowledge of enterprise security, data governance, entitlements, PII, and audit controls.
• Experience building reusable AI platforms and/or front-end development with React or Angular.