AI Solution Architect

Experience

1015%2B years overall experience (with 5%2B 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

AI, ML & ML Ops Architecture

• 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

Generative AI & Agentic AI

• 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

Business Intelligence & Analytics

• 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

Stakeholder & Technical Leadership

• 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

Core Technical Skills

• 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

Tools & Technologies (preferred)

• 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)

Preferred Qualifications

• 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