Senior customer-facing AI solution architect for pre-sales and delivery, owning AI/ML, GenAI and Agentic AI solutions on AWS and Azure for enterprise customers.

About the Company Rapyder Cloud Solutions is an agile cloud consulting and managed services company headquartered in Bangalore, with sales and support offices in Delhi and Mumbai. The company focuses on cloud computing solutions, big data, marketing and commerce, DevOps and managed services, and positions itself as a strategic cloud consulting partner. Rapyder's solutions are designed to be seamless, secure and scalable, helping customers reduce costs, streamline business processes and gain business advantages. The firm is expanding its AI practice and is hiring senior technical talent to help shape and win enterprise AI opportunities across India.

Role Overview This is a senior, customer-facing pre-sales and solution architecture role within the AI Solutions Team. The Enterprise Senior AI Solution Architect will translate complex customer business problems into outcome-driven AI solutions and support those solutions through delivery. The role sits at the intersection of cloud infrastructure, AI/ML platforms, enterprise pre-sales and delivery. You will partner with Business Development, Tech Sales and Delivery teams to shape and win large AI opportunities, lead technical discovery, own solution architecture and RFP responses, build PoCs and set delivery up for success. You will also mentor Solution Architects and act as a senior technical voice with CTO/CIO/CDO stakeholders at mid-market and enterprise customers. The position is based in Bangalore and requires 5+ years of relevant experience, with joining immediate to 45 days.

Key Responsibilities

• Solution Design & Architecture: Architect end-to-end AI/ML, GenAI and Agentic AI solutions on AWS and Azure, with GCP as a plus. Cover data pipelines, model training and fine-tuning, RAG and agent workflows, inference infrastructure, integration layers, security, observability and FinOps.
• Pre-Sales Leadership: Lead technical discovery, solution workshops and architecture review sessions with CTO/CIO/CDO and AI leads. Qualify opportunities, shape win themes and own the technical strategy for strategic deals.
• Proposal, RFP & Commercials: Own the technical response for RFPs and proposals, including architecture documents, delivery approach, realistic effort and team estimates, assumptions, risks and SOW scoping.
• Proof of Concept & Pilots: Define success criteria and build or lead PoCs and pilots that validate feasibility and business value using AWS SageMaker and Bedrock, Azure AI Foundry, Copilot or equivalent platforms. Guide the path from PoC to production.
• Delivery Assurance & Handover: Bring delivery experience into pre-sales by validating feasibility and estimates with delivery teams, running structured handover reviews, and staying engaged post-signoff to protect architectural integrity, resolve escalations and support customer acceptance on key engagements.
• Customer Advisory: Act as a trusted AI advisor by running AI readiness and data maturity assessments, mapping business goals to AI roadmaps, identifying quick wins, and proposing phased implementation plans with clear ROI and success metrics.
• Responsible AI & Governance: Embed security, data privacy, guardrails, evaluation and Responsible AI practices into every solution. Address compliance, data residency and sovereign cloud requirements in regulated industries.
• Team Mentoring: Coach and review the work of Solution Architects and Engineers. Build reusable reference architectures, solution accelerators, estimation templates and playbooks that raise the quality and speed of the practice.
• Thought Leadership: Contribute to case studies, whitepapers and knowledge bases, and represent Rapyder at customer events, webinars and partner forums such as AWS and Microsoft.
• Market Intelligence: Track AI platform and ecosystem updates across AWS, Azure, GCP, NVIDIA, open-source LLMs and agent frameworks, and proactively bring relevant innovations into customer conversations.

Tech Stack The role requires hands-on exposure to AWS services such as SageMaker, Bedrock, Lambda, Step Functions, S3 and Glue, or Azure AI/ML services such as Azure AI Foundry, Azure ML and Data Factory. Strong working knowledge is expected in Large Language Models, Retrieval-Augmented Generation, vector databases, prompt engineering, evaluation, and AI agent frameworks such as LangChain, LlamaIndex and AutoGen. The architect should be comfortable with end-to-end data and AI pipelines, model serving, monitoring, MLOps and LLMOps lifecycle, CI/CD for ML, model versioning, drift detection, guardrails and cost optimisation. Good-to-have exposure includes GCP, NVIDIA platforms such as NIM, NeMo and Jetson, open-source LLMs such as Mistral, LLaMA and Falcon, Edge AI, Vision AI or Physical AI use cases, sovereign cloud requirements, enterprise data governance, security architecture, compliance frameworks, Agile delivery and Agentic AI interoperability patterns such as MCP and A2A.

Candidate Profile Candidates should have 5+ years of experience in cloud solution architecture, AI/ML pre-sales or enterprise technology consulting, with a proven track record of designing and winning enterprise-scale AI/ML engagements. Prior experience as a Delivery Engineer or Technical Lead on cloud and AI/ML projects is important, including owning technical delivery, managing scope and risks, and taking solutions from design to production. The ideal candidate combines strong architecture judgement with confident communication and stakeholder management skills, and can present to both technical architects and business executives. Experience mentoring junior architects and collaborating across Sales, Delivery and Partner teams is expected. A bachelor's degree in Computer Science, Engineering or a related field is required; an advanced degree is a plus. Certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning Specialty or equivalent Azure certifications are advantageous.

Good to Have Exposure to Edge AI, Vision AI or Physical AI use cases in Manufacturing, Retail or Logistics; experience with NVIDIA platforms such as NIM, NeMo and Jetson; knowledge of sovereign cloud and data residency regulations; familiarity with open-source LLM fine-tuning and deployment pipelines; understanding of enterprise data governance, security architecture and compliance frameworks; experience with Agile delivery, project governance and Agentic AI interoperability patterns.

5+ years in cloud solution architecture, AI/ML pre-sales or enterprise technology consulting. Hands-on with AWS SageMaker/Bedrock or Azure AI/ML. Strong knowledge of LLMs, RAG, vector databases, prompt engineering, AI agent frameworks, MLOps/LLMOps, RFP responses, effort estimation and stakeholder management. Bachelor's degree required; advanced degree and AWS/Azure certifications preferred.

Full-time role with high visibility across pre-sales, delivery and partner teams; opportunity to shape enterprise AI solutions, mentor architects and work with CTO/CIO/CDO stakeholders.