Solution Architect

Job Description Architecting the Future: Agentic AI & Enterprise Transformation Join us in shaping the next wave of enterprise innovation through Generative and Agentic AI. We are seeking a pragmatic futurist and business-savvy technologist to redefine how enterprises operate in the AI-first era. You will lead the design, adoption, and scaling of Generative and Agentic AI ecosystems for our most strategic clients. This role blends advisory, hands-on solutioning, and practice-building leadership to ensure AI delivers tangible, industry-specific business outcomes. Core Responsibilities - Architect & Implement Enterprise AI Ecosystems Design and implement modular, scalable AI platforms that integrate Large Language Models (LLMs), Small Language Models (SLMs), and multi-agent orchestration. Ensure architectures are cloud-native, secure, and industry-compliant. - Drive AI Strategy Serve as the anchor architect for major client accounts. Lead C-level discussions to define AI roadmaps that link technology to measurable business outcomes. Influence long-term investment strategies. - Industry-Specific AI Solutions Envision, Design and Deliver verticalized AI use cases across one or more industries, including Banking & Financial Services, Consumer Goods, Energy & Utilities, Healthcare, Insurance, Life Sciences, Logistics, Manufacturing, Media, Retail, Telecom, and Travel & Hospitality. - Develop, Train & Optimize Models Lead end-to-end model lifecycle: data preparation, training, fine-tuning, deployment, monitoring, and continuous improvement. Balance LLM vs. SLM adoption for cost, latency, and performance optimization. - MLOps & LLMOps Leadership Establish enterprise standards for MLOps/LLMOps pipelines (CI/CD, monitoring, observability, drift detection, compliance). Build agent lifecycle governance frameworks for scalable, auditable AI systems. - People Leadership & Practice Building Mentor and grow a community of architects and engineers. Build capability squads in GenAI/Agentic AI. Shape the company's AI practice, including skills development, hiring strategy, and succession planning. - Ecosystem & Partner Engagement Build and leverage strategic partnerships with hyperscalers (AWS, Azure, GCP), ISVs, and AI startups. Co-develop joint offerings, influence partner roadmaps, and co-sell AI solutions into strategic accounts. - Innovation & Thought Leadership Publish white papers, frameworks, and patents. Lead executive roundtables and contribute to the Tech Radar, ensuring the firm shapes the AI conversation in the market. Required Skills & Experience - 18+ years in IT & architecture, with clear progression from hands-on engineering (Java/.NET preferred) into enterprise architecture leadership. - 5+ years in AI/ML, with 1+ year in Generative & Agentic AI (LLMs, SLMs, multi-agent orchestration). - Model Training Expertise: Fine-tuning (SFT, RLHF, LoRA/QLoRA), RAG, evaluation pipelines. - Hyperscaler Certifications: Architect-level expertise in at least two (AWS, Azure, GCP). - MLOps/LLMOps Mastery: CI/CD pipelines, monitoring, observability, compliance, AI cost governance. - CxO Advisory: Proven experience leading executive AI strategy discussions with Fortune 500 clients. - Governance Expertise: Familiar with AI RMF (NIST), EU AI Act, Responsible AI practices. - People Leadership: Experience mentoring teams and building cross-functional AI capability practices. - Ecosystem Influence: Track record shaping AI initiatives through partner alliances (hyperscalers, startups, ISVs). Good to have. - Publications, patents, or open-source contributions in Agentic AI, LLMOps, or model compression/distillation. - Recognized thought leadership (conferences, panels, media interviews). - Industry domain depth in at least one vertical: Banking & Payments, Consumer Goods, Energy & Utilities, Healthcare, Insurance, Life Science, Logistics, Manufacturing, Media, Retail, Telecom, Travel & Hospitality - Experience with AgentOps, model evaluation frameworks, and AI observability tooling. Functional Competencies - Business Acumen: Identify and execute high-value AI transformations across industries. - Consultative Mindset: Convert PoCs/PoVs into long-term transformation programs. - Practice Builder: Mentor, hire, and scale AI architecture talent pools. - Ecosystem Shaper: Drive co-innovation with hyperscalers, startups, and ISVs. - Pragmatic Execution: Balance build-vs-buy, deliver under pressure, and navigate enterprise politics. - Translation & Storytelling: Distill complex AI concepts into clear executive-ready narratives.