About The Position

ClearSource is looking for a Director of Innovation who has gone beyond experimenting with AI — someone who has shipped real products and tools powered by large language models (LLMs) inside a company. You will own our AI roadmap end-to-end: identifying high-impact use cases, building or overseeing the tools that bring them to life, and driving adoption across the business. This is a player-coach role. You will lead a small team while staying hands-on technically — scoping solutions, guiding architecture decisions, and rolling up your sleeves when needed. You report to a VP/SVP and will work cross-functionally with Operations, Technology, and Client Services to embed AI into the fabric of how ClearSource operates.

Requirements

  • The most important thing: you have actually built and launched LLM-powered products inside a company — not just used AI tools, but built them.
  • 5+ years in a product, engineering, or technology leadership role.
  • Demonstrated track record of shipping AI/LLM-based tools or products into production (not just proofs of concept).
  • Hands-on experience with LLM APIs (OpenAI, Anthropic Claude, Google Gemini, or open-source equivalents) and common orchestration frameworks (LangChain, LlamaIndex, or similar).
  • Experience managing or mentoring a technical team.
  • Ability to bridge the gap between technical implementation and business stakeholder communication.

Nice To Haves

  • Background in BPO, contact center, or tech-services environments — you understand the operational context we work in.
  • Experience with RAG (Retrieval-Augmented Generation), fine-tuning, or prompt engineering at scale.
  • Familiarity with enterprise AI governance frameworks and responsible AI principles.
  • Prior work in a multi-geo or global team environment.

Responsibilities

  • Build & Ship AI Products
  • Lead the design, development, and deployment of LLM-powered tools — from internal automation to client-facing solutions.
  • Translate ambiguous business problems into scoped, buildable AI products with clear success metrics.
  • Own the full product lifecycle: ideation → prototype → pilot → scaled rollout.
  • Lead a Small Team
  • Hire, manage, and develop a small team of AI engineers, analysts, or product specialists.
  • Set technical direction, prioritize the roadmap, and hold the team accountable to delivery timelines.
  • Foster a culture of fast experimentation — build, test, learn, iterate.
  • Drive Organizational Adoption
  • Partner with department heads to identify where AI can reduce cost, improve quality, or create new value.
  • Build internal enablement programs so non-technical teams can leverage AI tools confidently.
  • Champion responsible AI practices — governance, bias awareness, data privacy, and security.
  • Stay Ahead of the Curve
  • Monitor the LLM ecosystem (OpenAI, Anthropic, Google, open-source models) and evaluate new capabilities for business applicability.
  • Build and maintain relationships with key AI vendors and platform partners.
  • Report progress, ROI, and forward-looking strategy to senior leadership.
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