What are the responsibilities and job description for the AI Solution Architect position at Jobs via Dice?
Experience
1015 years overall experience (with 5 years in AI/Data
Architecture roles)
Job Summary
We are seeking a highly skilled AI Solution Architect with
deep expertise in Data Architecture, AI/ML platforms, and Generative AI
solutions, to design and deliver scalable, secure, and enterprise-grade data
and AI solutions.
The ideal candidate will have strong hands-on experience
across datalake house architectures, modern BI platforms, ML/ML Ops,
Conversational Analytics, Generative AI, and Agentic AI frameworks, and will
work closely with business, data engineering, and AI teams to drive end-to-end
AI-led transformation.
Key Responsibilities
Data & Platform Architecture
1015 years overall experience (with 5 years in AI/Data
Architecture roles)
Job Summary
We are seeking a highly skilled AI Solution Architect with
deep expertise in Data Architecture, AI/ML platforms, and Generative AI
solutions, to design and deliver scalable, secure, and enterprise-grade data
and AI solutions.
The ideal candidate will have strong hands-on experience
across datalake house architectures, modern BI platforms, ML/ML Ops,
Conversational Analytics, Generative AI, and Agentic AI frameworks, and will
work closely with business, data engineering, and AI teams to drive end-to-end
AI-led transformation.
Key Responsibilities
Data & Platform Architecture
- Design and own end-to-end data architectures including ingestion, processing, storage, governance, and consumption layers
- Define scalable data platforms supporting batch, streaming, and real-time analytics
- Establish data governance, metadata management, data quality, lineage, and security frameworks
- Design ML/AI architectures supporting model training, deployment, monitoring, and lifecycle management
- Define and implement ML Ops frameworks (CI/CD for ML, feature stores, model registries, observability)
- Collaborate with data scientists to productionize ML models at scale
- Evaluate and recommend ML frameworks, tools, and best practices
- Architect and implement Generative AI solutions using LLMs (e.g., text, code, embeddings, multimodal use cases)
- Design Conversational Analytics and AI-powered BI solutions
- Build and evaluate Agentic AI platforms, including autonomous agents, orchestration frameworks, and tool integrations
- Lead solution evaluations, PoCs, and vendor/tool assessments for GenAI and Agent-based systems
- Design modern BI and analytics platforms enabling self-service analytics and AI-driven insights
- Integrate BI tools with data Lakehouse and AI layers
- Enable semantic layers, metrics definitions, and governed analytics
- Ensure architectures follow best practices for security, scalability, performance, and cost optimization
- Partner with business leaders to translate business requirements into AI-driven solutions
- Lead technical design reviews and architecture governance
- Mentor engineers, architects, and data scientists
- Create architecture blueprints, reference architectures, and technical documentation
- Strong experience in Data Architecture & Data Platforms
- Hands-on expertise in Data Lakehouse architectures
- Deep understanding of end-to-end data management
- Experience with modern BI platforms and analytics ecosystems
- Strong background in AI/ML architecture and MLOps
- Proven experience in Conversational Analytics and Generative AI
- Hands-on exposure to Agentic AI platforms, frameworks, and evaluations
- AI/ML: TensorFlow, PyTorch, scikit-learn, LLM frameworks
- MLOps: CI/CD, feature stores, model registries, monitoring tools
- Data: SQL, Python, Spark, Kafka
- BI: Looker, Tableau, Power BI (or equivalent)
- Bachelors or Masters degree in Computer Science, Data Science, Engineering, or related field
- Experience working in large-scale enterprise or consulting environments
- Strong communication and stakeholder management skills