Technical Product / Program Leader

Saicon; Georgia; On-site; USD 180,000 - 230,000; Full time

Job summary

Saicon is seeking a Technical Product / Program Leader to build our next generation of a trusted, measurable, scalable and AI-enabled knowledge ecosystem. You will lead both technical Knowledge Management and content/governance resources at the intersection of Knowledge Management, Generative AI, automation, information architecture and technical product leadership.

You will translate business needs into technical solutions, moving capabilities from concept through prototype, deployment and

Qualifications

• Experience taking enterprise AI solutions from concept through production and adoption.
• Strong knowledge of LLMs, Retrieval-Augmented Generation (RAG), enterprise/semantic search and agentic architectures.
• Experience designing or directing agent workflows, retrieval and grounding approaches, including how AI accesses trusted enterprise information.
• Experience integrating enterprise knowledge and data through APIs, connectors, retrieval pipelines or similar integration approaches.
• Strong understanding of knowledge architecture, taxonomy, metadata, content lifecycle and information governance.
• Experience measuring content quality, retrieval effectiveness, AI reliability and/or user adoption.
• Demonstrated ability to lead complex cross-functional technology programs and translate business requirements into scalable solutions.

Responsibilities

• Define KPIs for content accuracy, freshness and AI readiness and establish governance automation.
• Define the architecture and roadmap for agentic capabilities; lead prototyping of AI agents grounded in enterprise knowledge.
• Design how multiple agents and AI capabilities work together to deliver trusted enterprise knowledge.
• Establish retrieval, grounding, integration, security and evaluation standards for production-ready agentic capabilities.
• Collaborate with engineers to translate business needs into scalable solutions and guide implementation.

Skills

Enterprise AI

Generative AI

Agentic AI

Cross-functional

Architecture

APIs

Knowledge mgmt

AI reliability

Governance

Prototyping

Python

SQL

Tools

Python

SQL

Low-code

Job description

We are looking for a Technical Product / Program Leader to build the next generation of our commercial knowledge capability, moving us from a traditional knowledge repository to a trusted, measurable, scalable and AI-enabled knowledge ecosystem.

This role will lead both technical Knowledge Management and content/governance resources and will work at the intersection of Knowledge Management, Generative AI, automation, information architecture and technical product leadership.

This is not a traditional Knowledge Management maintenance role. We need a leader who can set the strategy and get it built, translating business needs into technical solutions and moving capabilities from concept through prototype, deployment and measurable adoption.

What You Will Deliver in 12 Months

1. Make our knowledge measurable and trustworthy

Establish how we measure the health and reliability of commercial knowledge and use automation to improve it.

You will:

• Define KPIs for content accuracy, freshness, ownership, review adherence, reliability and AI readiness.
• Establish a baseline showing how much of our current knowledge can be trusted and where intervention is required.
• Measure and advance content review and governance automation, reducing manual effort for content owners.
• Create actionable reporting that identifies healthy, stale, unowned or unreliable content and drives continuous improvement.

Success looks like: We can confidently answer how much of our commercial knowledge we can trust and whether it is ready for use by both people and AI.

2. Build our agentic knowledge capability

Transform the Knowledge Hub from a repository into an AI-enabled experience where intelligent agents can retrieve, connect and deliver trusted enterprise knowledge.

You will:

• Define the architecture and roadmap for agentic capabilities.
• Lead or directly support the development and prototyping of AI agents grounded in enterprise knowledge.
• Design how multiple agents and AI capabilities work together, rather than creating disconnected AI use cases.
• Establish the retrieval, grounding, integration, security and evaluation standards required to move agentic capabilities into production.
• Work directly with technical resources to translate emerging AI capabilities into practical commercial use cases.

Success looks like: We have moved from discussing AI to delivering usable agentic capabilities operating against trusted commercial knowledge.

3. Create a scalable enterprise knowledge framework

Turn what we build for Product Commercialization into a repeatable framework that other internal organizations can use to contribute trusted knowledge, one trusted source.

Your team will deliver:

• Define the onboarding and adherence model for internal knowledge providers.
• Establish standards for content review, metadata, taxonomy, ownership, lifecycle and governance.
• Create a scalable model that allows teams to maintain their own knowledge without creating unsustainable manual work for the central KM team, but connect this back to the reporting so we are aware and can action.
• Ensure trusted knowledge can ultimately be consumed through search, enterprise workflows and AI/agentic experiences.

Success looks like: We have moved from managing a Knowledge Hub to operating a scalable enterprise knowledge framework that other teams can adopt.

What You Bring

We are looking for someone who combines technical product/program leadership with deep knowledge and AI fluency.

Required Experience

• Demonstrated experience taking enterprise AI, Generative AI or agentic solutions from concept through production and adoption.
• Strong working knowledge of LLMs, Retrieval-Augmented Generation (RAG), enterprise/semantic search and agentic architectures.
• Experience designing or directing agent workflows, retrieval and grounding approaches, including how AI accesses trusted enterprise information.
• Experience integrating enterprise knowledge and data through APIs, connectors, retrieval pipelines or similar integration approaches.
• Strong understanding of knowledge architecture, taxonomy, metadata, content lifecycle and information governance.
• Experience measuring content quality, retrieval effectiveness, AI reliability and/or user adoption.
• Sufficient technical depth to work directly with engineers and architects, challenge technical decisions and translate business requirements into scalable solutions.
• Demonstrated ability to lead complex cross-functional technology programs and technical resources.

You do not need to be the team's primary software engineer. You do need enough technical depth to sit alongside engineers and architects, understand the architecture, challenge it when necessary and actively guide how a solution gets built.

Technology Proficiency

Experience across a combination of:

• AI & Retrieval: LLMs, RAG, agentic AI, multi-agent orchestration, semantic search, embeddings, vector search, AI grounding and evaluation.
• Integration & Data: APIs, JSON, enterprise connectors, structured/unstructured data, authentication/permissions and cloud architecture.
• Microsoft Ecosystem: Microsoft 365, SharePoint, Copilot Studio, Power Platform, Power Automate, Microsoft Graph and/or Azure AI.
• Prototyping: Working knowledge of Python, SQL, low-code development, APIs and modern AI prototyping techniques.

What Will Differentiate You

The strongest candidates will be able to demonstrate something they have personally taken through:

Problem → Architecture → Prototype → Production → Adoption → Measurement

We want to understand what you built or directed, how you grounded AI against trusted enterprise information, how you addressed governance and security, and how you measured whether the solution delivered value.

We are not looking for someone to simply administer today's Knowledge Management environment. We are looking for someone capable of defining and building what comes next.