Senior Agentic/Gen AI Expert (Engagement Manager)

Fractal Analytics•New York, NY

1d•$185,000•Onsite

About The Position

Fractal Analytics is a global, AI‑first company and strategic partner to Fortune 500 organizations. AI is Fractal’s core business. For over 25 years, Fractal has helped enterprises apply advanced analytics and AI to improve decision‑making at scale. Fractal’s Healthcare & Life Sciences (Pharma) practice supports global pharmaceutical organizations across commercial, R&D, supply chain, and enterprise functions. We work with many of the world’s largest pharma companies to design, build, and scale production‑grade AI and GenAI solutions that deliver measurable business and patient impact. Join our team and shape the future of Pharma & Life Sciences through groundbreaking technology solutions! This position is not eligible for Immigration Sponsorship at this time.

Requirements

10+ years of hands‑on experience in AI, machine learning, or advanced analytics, with clear progression into senior technical or architectural leadership roles.
Demonstrated deep expertise in agentic AI and multi‑agent systems, including real‑world experience designing, evaluating, or governing such systems in enterprise contexts.
Strong foundation in GenAI / LLM architectures, including orchestration, retrieval‑augmented generation, tool‑using agents, and system‑level design considerations.
Prior experience engaging directly with enterprise technical teams (architecture, data platforms, security) and navigating complex organizational environments.
Exceptional ability to communicate technical concepts to non‑technical audiences, particularly senior business and executive stakeholders.
Comfort operating in fast‑paced, ambiguous discovery settings where ideas must be evaluated and refined live.

Nice To Haves

Consulting, advisory, or pre‑sales experience strongly preferred
Pharma or life sciences experience is helpful but not required.

Responsibilities

Serve as the lead technical expert on agentic AI and GenAI across the engagement, with demonstrated depth in multi‑agent system design, orchestration patterns, and LLM‑based architectures.
Evaluate, critique, and stress‑test proposed AI concepts and architectures in real time with the client’s enterprise architecture, data, and platform teams.
Distinguish viable, production‑ready agentic patterns from theoretical or immature approaches, providing clear guidance on feasibility, risks, and tradeoffs.
Actively participate in discovery workshops involving cross‑functional stakeholders spanning business, IT, analytics, and commercial operations.
Translate business problems surfaced in workshops into AI‑solvable framings, identifying where agentic AI, automation, and generative models can drive step‑change improvements.
Provide authoritative technical input during live discussions, helping steer conversations toward realistic and high‑value AI opportunities.
Collaborate with design and research specialists to map current‑state enterprise workflows.
Help redesign future‑state workflows using the engagement’s north‑star framing: “25 steps → 5 steps + 5 AI agents.”
Ensure proposed AI‑augmented processes align with enterprise constraints including data availability, security, compliance, scalability, and operating models common in regulated pharma environments.
Translate complex AI and LLM concepts into clear, business‑relevant language for senior non‑technical stakeholders.
Support synthesis of findings into an executive‑ready AI roadmap, prioritizing opportunities by impact, feasibility, and organizational readiness.
Help ensure final recommendations are defensible, pragmatic, and grounded in technical reality, not hype.