Senior AI Engineer; Agentic Systems

Senior AI Engineer (Agentic Systems)

The Senior AI Engineer will design and deliver enterprise-grade AI agent solutions that automate document ingestion, orchestrate workflows, and augment decision-making across risk, finance, and governance domains. This role focuses on leveraging and integrating existing LLM platforms to build scalable, production-ready agent systems. The position requires strong system design, agent orchestration, and pragmatic application of AI to drive measurable operational efficiency.

Key Responsibilities

• Design and deliver enterprise-grade AI agent solutions for automation and decision augmentation.
• Leverage and integrate existing LLM platforms to build scalable, production-ready agent systems.
• Embed AI into engineering and product delivery workflows without developing foundational models.
• Apply strong system design and agent orchestration to drive operational efficiency.
• Design end-to-end AI workflows, including prompting, retrieval, tool integration, and output validation.
• Utilize AI-assisted development tooling to accelerate engineering productivity and solution design.
• Define and measure outcomes such as efficiency gains, cost reduction, and adoption metrics.
• Engage with stakeholders to translate business problems into pragmatic AI solutions.

Required Qualifications

Experience:

• 5–8+ years of experience in software engineering, AI solution engineering, or applied data workflows.
• Proven experience building AI agents or agentic workflows using existing LLMs (task orchestration, tool use, memory, workflow chaining).
• Hands-on experience with AI-assisted development tooling (e.g., Git Hub Copilot, Copilot Studio, or equivalent).
• Experience with cloud-native architectures and integration into enterprise environments and tooling.

Technical

Skills:

• Strong Python engineering skills and experience building production-grade services and APIs.
• Proficiency in prompt engineering, grounding, and guardrails to ensure reliability and control.
• Strong understanding of RAG patterns, document ingestion, and unstructured data processing.
• Knowledge of Artificial Intelligence/Machine Learning principles.
• Experience with Teradata.

Preferred Qualifications

• Experience designing multi-agent or orchestrated agent systems for enterprise workflows.
• Experience building interactive copilots or embedded AI assistants within engineering or operational tools.
• Familiarity with agent evaluation techniques, human-in-the-loop validation, and iterative improvement loops.
• Experience applying AI to workflow automation, operational efficiency, or service delivery transformation.
• Knowledge of Responsible AI, governance, and enterprise risk considerations.
• Track record of driving AI adoption across engineering or product organizations.
• Experience operating in product-centric, outcome-driven delivery models.