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Job Description: Generative AI (GenAI) Solution Architect - Pre-Sales Team ( 2 openings- 1 East Coast, 1 West) Job Summary We are seeking a highly skilled and dynamic Generative AI Solution Architect to join our pre-sales team. In this role, you will be the technical evangelist and strategic advisor for GenAI initiatives, focusing on agentic AI solutions that enable autonomous, intelligent systems. You will leverage your deep expertise in architectural patterns, emerging trends, and GenAI cloud platforms to design and pitch innovative solutions. The ideal candidate thrives in client-facing environments, leading workshops with C-level executives and senior stakeholders, while demonstrating both technical depth and broad industry knowledge. This position requires excellent communication skills, a consultative mindset, and flexibility to travel for on-site client meetings and engagements. This is a high-impact role where you will collaborate closely with sales, engineering, and product teams to convert client needs into compelling GenAI proposals, proofs-of-concept (POCs), and roadmaps. If you are passionate about pushing the boundaries of AI and have a proven track record in pre-sales architecture, we invite you to apply. Key Responsibilities Drive Agentic AI Solutioning: Lead the design and architecture of agentic AI systems, including multi-agent frameworks, autonomous decision-making workflows, and integration with enterprise ecosystems. Develop end-to-end solutions that incorporate reasoning engines, tool-calling mechanisms, and adaptive learning to address client-specific use cases in areas like automation, personalization, and predictive analytics. Architectural Expertise and Innovation: Stay at the forefront of GenAI architectural patterns (e.g., Retrieval-Augmented Generation (RAG), transformer-based models, fine-tuning strategies, and hybrid architectures). Evaluate and recommend the latest trends such as multimodal AI, edge deployment, ethical AI governance, and scalable inference techniques. Provide thought leadership on integrating GenAI with existing IT landscapes, ensuring security, scalability, and cost-efficiency. GenAI Cloud Platform Mastery: Design solutions leveraging major GenAI cloud platforms, including AWS Bedrock, Azure OpenAI Service, Google Vertex AI, Anthropic's Claude, and others. Conduct platform comparisons, optimize for performance and cost, and guide clients on migration, deployment, and orchestration strategies (e.g., using Kubernetes, serverless computing, or API gateways). Client Workshops and Engagements: Facilitate interactive workshops, discovery sessions, and technical deep-dives with senior client stakeholders (e.g., CIOs, CTOs, and business leaders). Translate complex technical concepts into business value, demonstrating depth in specific domains (e.g., NLP, computer vision) and breadth across industries (e.g., finance, healthcare, retail). Use storytelling, prototypes, and data-driven insights to build consensus and accelerate deal closure. Pre-Sales Support: Collaborate with sales teams to create customized proposals, RFPs/RFIs responses, and solution blueprints. Develop POCs, demos, and MVPs to showcase GenAI capabilities, iterating based on client feedback. Conduct competitive analysis and risk assessments to position our solutions effectively. Knowledge Sharing and Team Enablement: Mentor junior architects and sales engineers on GenAI best practices. Contribute to internal knowledge bases, whitepapers, and webinars. Participate in industry conferences and forums to represent the company as a GenAI expert. Travel and Client Interaction: Be prepared for up to 50% travel to client sites for meetings, workshops, and on-site collaborations, including domestic and international destinations as needed. Required Qualifications and Experience Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. Advanced certifications in AI/ML (e.g., AWS Certified Machine Learning Specialty, Google Professional Machine Learning Engineer) or cloud architecture are highly preferred. Professional Experience: • 8+ years in solution architecture, with at least 4 years focused on AI/ML, including hands-on experience in GenAI projects. • Proven track record in pre-sales or consulting roles, driving multimillion-dollar deals through technical expertise. • Demonstrated success in agentic AI implementations, such as building AI agents for task automation, conversational systems, or reinforcement learning-based applications • Experience leading client workshops and presentations for executive audiences, with a portfolio of case studies or references. Technical Skills: • Deep knowledge of GenAI frameworks and tools (e.g., LangChain, LlamaIndex, Hugging Face Transformers, OpenAI APIs). • Proficiency in programming languages like Python, and familiarity with DevOps tools (e.g., Docker, Terraform, CI/CD pipelines). • Expertise in cloud-native GenAI services, including model training, inference optimization, and data pipelines (e.g., using Apache Airflow or Kubeflow). • Understanding of architectural patterns like microservices, event-driven systems, and zero-trust security in AI contexts. • Awareness of ethical AI considerations, bias mitigation, and regulatory compliance (e.g., GDPR, AI Act). Soft Skills: • Excellent communication and presentation skills, with the ability to articulate technical details to non-technical audiences and vice versa. • Strong problem-solving abilities, with a consultative approach to uncovering client pain points and proposing innovative solutions. • Executive presence and interpersonal skills to build trust with senior stakeholders. • Adaptability and resilience in fast-paced, ambiguous environments. • Willingness to travel extensively, including occasional international trips. Preferred Qualifications: • Experience in specific industries such as finance, healthcare, manufacturing, or e-commerce. • Publications, patents, or contributions to open-source GenAI projects. • Familiarity with emerging trends like AI agents in Web3, quantum-inspired AI, or sustainable AI computing. • Multilingual capabilities to support global clients.