Senior Gen AI Solutions Architect

About the Role

Key Responsibilities

• Design end-to-end AI system architectures integrating GenAI and Agentic capabilities
• Build solutions for on-premise data centers and public cloud platforms
• Evaluate and implement agent-based orchestration frameworks (e.g., CrewAI, AutoGen, LangGraph)
• Lead development of Retrieval-Augmented Generation (RAG) pipelines and hybrid inferencing strategies
• Advise on model governance, system explainability, and responsible AI practices
• Collaborate with data scientists and MLOps teams on model training and deployment
• Conduct architecture reviews and present multi-agent design patterns and emerging tools
• Select appropriate GenAI technologies (open-source, proprietary, cloud, hybrid)
• Lead solution blueprinting, technical feasibility assessments, and roadmapping
• Act as a GenAI thought leader in strategic client engagements
• Conduct discovery sessions, co-creation workshops, and C-suite presentations
• Translate complex AI capabilities into business outcomes, ROI estimates, and transformation roadmaps
• Build trust and credibility as a technical SME in GenAI and Agentic AI
• Advocate for Responsible AI principles and ensure compliance across deployments
• Implement guardrails, governance frameworks, and security protocols for GenAI platforms
• Address risk and compliance across multiple customer environments
• Create reusable playbooks, frameworks, and GenAI solution kits for financial services
• Mentor internal teams and conduct enablement sessions
• Stay current on GenAI advancements, industry regulations, and AI risk trends

Requirements

• 15+ years in enterprise technology, consulting, or solution architecture
• 3+ years of hands-on experience in GenAI or LLM-based solution design
• Proven experience designing AI solutions for banks, asset managers, insurers, or fintechs
• Deep expertise with LLMs (OpenAI, Mistral, Claude, LLaMA), embeddings, and vector databases (FAISS, Pinecone)
• Proficiency with GenAI tools (LangChain, LlamaIndex, Transformers) and Agentic frameworks (AutoGen, CrewAI, AutoGPT)
• Strong command of Python and cloud platforms (Azure, AWS, Google Cloud Platform)
• Excellent communication and stakeholder engagement skills
• Strong grasp of security, scalability, observability, and compliance in AI systems

Nice to Have

• Experience with multi-agent design patterns
• Knowledge of AI industry regulations and responsible AI practices
• Experience in financial services, healthcare, manufacturing AI applications

Qualifications

• Educational background not explicitly specified

Benefits & Perks

• Not specified in the description