Need proven enterprise-grade experience with agentic AI architectures -
not theoretical knowledge, but real deployments at scale. Specifically, we are looking for expertise across
multi-agent orchestration (e.g. AutoGen, Semantic Kernel, LangGraph or similar), LLM evaluation frameworks
including LLM-as-a-judge methodologies, content safety tooling and responsible AI practices, and strong data
science foundations to support model selection, evaluation, and performance analysis.
Product and Functional Skills
You'll be embedded in a team building complex agentic AI systems from the ground up, contributing across
design, development, and deployment. This includes architecting and implementing multi-agent orchestration
frameworks, integrating LLM-based evaluation pipelines (LLM-as-a-judge), and ensuring robust content safety
practices are baked into the solution.
Experience working in professional services or M&A technology environments is a strong advantage. Given the
caliber expected, you should be comfortable navigating ambiguity and helping define the approach, not just
executing against a pre-built spec.
Describe any Specific Requirements
This is a high-impact, first-of-its-kind initiative set to transform how a major professional services firm
approaches mergers and acquisitions. The work is genuinely novel, technically demanding, and will require
someone who thrives at the frontier of enterprise AI. Only candidates with deep, demonstrable hands-on
experience need apply.
This is one of those genuinely rare opportunities - a greenfield problem, a marquee client, and a chance to do
something that hasn't been done before. If you're at the top of your field in agentic AI and want work that
matches that level, this is worth a conversation.
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