Business Analyst — Agentic AI

Responsibilities

• Design and implement NLP/LLM solutions to analyze and categorize SAS scripts by business relevance, regulatory impact, and technical complexity.
• Use Generative AI to auto-generate metadata tags (ownership, data lineage, purpose) for script inventories.
• Build agentic AI components to detect redundant scripts, code overlaps, and migration risks; develop recommendation engines to prioritize scripts for migration or retirement.
• Create algorithms and consolidation strategies to optimize migration scope and reduce effort.
• Integrate solutions with Azure AI services (OpenAI, Cognitive Services, ML Studio) and set up Azure AI sandboxes for proofs-of-concept.
• Ensure AI outputs comply with data governance and regulatory requirements (e.g., GDPR, IFRS 17) and implement traceability for audit-ready lineage mapping.
• Collaborate with cross-functional stakeholders (data engineers, compliance, operations, business SMEs) to validate models against pilot datasets and refine deliverables.
• Prepare technical documentation, model evaluation reports, and migration recommendations for senior stakeholders.

Requirements

• Minimum 5+ years in AI/ML engineering, focusing on Generative AI, Agentic AI, or NLP.
• Strong proficiency in Python for ML and data engineering tasks.
• Hands-on experience with PyTorch and/or TensorFlow.
• Practical experience with LLM frameworks (e.g., LangChain, LlamaIndex) and large-model orchestration.
• Demonstrable experience with Azure AI services (OpenAI, Cognitive Services, ML Studio) and Azure data tooling (Synapse, Data Factory).
• Familiarity with legacy analytics environments (SAS) and script migration/rationalization workflows.
• Solid SQL skills (joins, CTEs, optimization) and understanding of ETL/ELT processes and data warehousing.
• Domain experience in finance or insurance; understanding of regulatory and governance requirements.
• Bachelor’s degree in Computer Science, Data Science, Information Technology, or related field.
• Strong communication, stakeholder management, and problem-solving skills.

Preferred Qualifications

• Experience setting up Azure AI sandbox environments for PoC and pilot work.
• Certifications in Azure, ML, or data governance.
• Prior involvement in legacy modernization, script rationalization, or large-scale migration projects.
• Familiarity with metadata management, data lineage tooling, and audit/trail implementation.
• Exposure to building recommendation engines and algorithmic prioritization for migration planning.

Benefits

• Contract role with competitive compensation.
• Opportunity to lead AI-driven legacy modernization in a regulated finance/insurance environment.
• Hands-on access to Azure AI services and modern LLM toolchains for prototyping and PoCs.
• Collaboration with cross-functional teams and senior stakeholders for high-impact deliverables.

About the Company

Distinguished digital transformation consulting and technology firm specializing in AI-led modernization and cloud-native solutions for finance and insurance clients. The firm focuses on applying Generative AI, Agentic AI, and advanced NLP to automate legacy migrations, improve governance, and accelerate business outcomes.