Sr AI Solutions Arch

 Sr AI Solutions Arch

Denver, CO

Onsite 5 days.

Mission

Drive adoption of AI/GenAI across the organization by translating business problems into scalable AI solutionsand ensuring delivery from idea → production.

Core Responsibilities

• Define AI / GenAI strategy & roadmap
• Identify high-value use cases (automation, copilots, analytics, etc.) 
• Translate business needs → AI solution design (RAG, agents, ML models)
• Lead cross-functional execution (engineering, data, product, design) 
• Own end-to-end lifecycle (discovery → build → deploy → optimize) 
• Establish AI governance, standards, and best practices
• Track impact (ROI, adoption, performance metrics) 

 Primary Skills (Must-Have)

These were the “non-negotiables”:

1. AI / GenAI Expertise

• LLMs, RAG, copilots, NLP 
• Prompt engineering basics 
• Understanding of ML lifecycle 

2. Product Strategy Thinking

• Strong product management mindset 
• Roadmap creation & prioritization 
• Business problem decomposition 

3. Solution Architecture Awareness

• Ability to design end-to-end AI systems 
• APIs, data pipelines, integrations 
• Cloud-native patterns 

4. Execution Leadership

• Drive delivery across teams 
• Stakeholder management 
• Decision-making under ambiguity 

5. Technical Fluency

• Comfortable with: 

• Python / SQL (at least working level) 
• Data platforms (Snowflake, Databricks, etc.) 
• Cloud (Azure / AWS / Google Cloud Platform) 

Secondary Skills (Good-to-Have)

These made candidates stronger but weren’t strict requirements:

1. Hands-on GenAI Tooling

• LangChain / Semantic Kernel / vector DBs 
• Fine-tuning / embeddings familiarity 

2. Agile & Delivery Frameworks

• Scrum / SAFe 
• Product operating models 

3. Data & Analytics Depth

• Experimentation (A/B testing) 
• Metrics design for AI products 

4. UX for AI

• Conversational design 
• Human-in-the-loop systems 

5. Domain Experience

• Industry-specific AI use cases (finance, healthcare, etc.)