Providing innovative, comprehensive, and end-to-end information technology and workforce management solutions that empower businesses to achieve digital transformation, enhance operational efficiency, and drive sustainable growth

Job Description

We are seeking a Senior, hands-on Applied AI Engineer to support the development of an enterprise Generative AI platform for Fixed Income Institutional Lending. The platform enables AI-powered document extraction, enterprise search, embedded assistants, and automated business workflows.

This is a production engineering role, focused on building and operating scalable AI solutions rather than research or proof-of-concept development. The ideal candidate will combine strong software engineering and system design capabilities with deep hands-on experience in RAG, retrieval systems, GenAI applications, agentic workflows, and LLMOps.

Key Responsibilities

• Design and develop production-grade GenAI applications and reusable AI workflows across Lending business lines.
• Architect and implement RAG and advanced retrieval solutions, including embeddings, vector databases, chunking, semantic/hybrid search, metadata filtering, and re-ranking.
• Build AI-powered document ingestion and extraction pipelines with validation, confidence scoring, traceability, and human-in-the-loop review.
• Develop AI assistants and agentic workflows using tool/function calling, structured outputs, and enterprise data sources.
• Design scalable AI architectures covering models, retrieval, orchestration, APIs, data flows, and system performance.
• Establish LLMOps and AI evaluation practices, including prompt/version management, regression testing, observability, monitoring, and feedback loops.
• Troubleshoot production issues involving retrieval quality, hallucinations, model regressions, prompt changes, data quality, latency, and reliability.
• Implement enterprise AI solutions aligned with security, PII handling, access entitlements, governance, and auditability requirements.
• Participate in architecture and code reviews and contribute to reusable AI engineering standards and platform capabilities.
• Explain technical implementations, architectural decisions, trade-offs, and production challenges clearly to technical stakeholders.

Required Qualifications

• 5+ years of software engineering experience with strong hands-on development skills in Python or Java.
• 2+ years of dedicated GenAI experience developing and operating production AI solutions in an enterprise environment.
• Deep hands-on expertise in RAG architecture and retrieval systems.
• Strong knowledge of embeddings, vector databases, chunking, semantic search, hybrid search, metadata filtering, and re-ranking.
• Experience with advanced retrieval techniques such as multi-stage/multi-vector retrieval, late-interaction approaches such as ColBERT, and retrieval evaluation.
• Strong software architecture and system design capabilities with the ability to explain technical decisions and trade-offs.
• Proven experience building AI solutions from the ground up, rather than primarily integrating pre-built AI solutions or third-party APIs.
• Hands-on experience with RAG, agentic workflows, tool/function calling, structured outputs, and GenAI orchestration frameworks.
• Strong LLMOps experience, including evaluation, prompt/version management, regression testing, observability, monitoring, and feedback loops.
• Experience developing AI-driven document ingestion and extraction pipelines with measurable accuracy and quality.
• Experience supporting production AI systems and resolving issues related to model behavior, retrieval quality, prompts, data quality, reliability, and performance.
• Strong analytical and troubleshooting skills with the ability to reason about AI systems under the hood.
• Experience applying AI to enterprise use cases such as document intelligence, enterprise search, reconciliation, contracts/credit agreements, or natural-language-to-data applications.

Preferred Qualifications

• Experience in Financial Services, particularly Fixed Income or Institutional Lending.
• Experience working in regulated enterprise environments with strong security, governance, and data protection requirements.
• Experience with enterprise AI platforms and reusable AI capabilities.
• Experience with React or Angular.
• Familiarity with enterprise data security, PII protection, entitlements, governance, and auditability.
• Experience designing AI solutions that integrate with multiple enterprise data sources and business systems.
• Experience establishing AI engineering standards, reusable components, and platform-level capabilities.