Solution Architect

Requirements:

• 8-15 years of overall experience, with a significant portion in client-facing solution/technical architecture roles.
• Proven experience architecting and delivering enterprise data platforms on AWS, Snowflake, and/or Databricks.
• Strong hands-on exposure to GenAI technologies: LLM orchestration (LangChain, LangGraph or equivalent), RAG, Agentic AI/Deep Agents, knowledge graphs, and AI guardrails.
• Experience with AWS AI/ML services such as Bedrock, SageMaker, Bedrock Agents, along with core cloud services (ECS/EKS, Lambda, API Gateway, Step Functions, EventBridge, DynamoDB).
• Solid understanding of data engineering fundamentals — Apache Spark, Python, SQL/PL-SQL, and modern lakehouse/data mesh architecture patterns.
• Demonstrated experience in pre-sales: RFP/RFI responses, effort estimation, solution budgeting, and POV/POC development.
• Track record of driving measurable business value/revenue through architected AI or data solutions.
• Experience with self-service analytics enablement and onboarding large user bases (1,000+ users) onto governed data platforms.
• Familiarity with regulated industry environments (Life Sciences/GxP or similar) is a strong plus.
• Experience building or governing conversational AI/chatbot ecosystems is a plus.
• Strong stakeholder management and executive communication skills; ability to influence at leadership levels.
• Experience leading and mentoring cross-functional, multi-cultural engineering teams.

Preferred Certifications:

• AWS Certified Solutions Architect / Data Engineer / AI Practitioner / Generative AI (any combination).
• Microsoft Azure Fundamentals (or equivalent multi-cloud exposure).
• Agile / IBM Design Thinking or equivalent delivery methodology certifications.
• Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's preferred but not mandatory).