Enterprise Sr. AI Solution Architect

Team: AI - Solutions Team (Pre-sales)

Location: Bangalore   |   Experience: 5+ Years   |   Joining: Immediate to 45 Days

Rapyder is scaling its AI Practice, and we are looking for an Enterprise Sr. AI Solution Architect who can turn complex customer business problems into outcome-driven AI solutions - and who has also seen those solutions through delivery. This is a high-visibility, customer-facing role at the intersection of cloud infrastructure, AI/ML platforms, enterprise pre-sales and delivery.

You will partner with our Business Development, Tech Sales and Delivery teams to shape and win large AI opportunities: leading technical discovery, owning solution architecture and RFP responses, building PoCs, and setting up delivery 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.

If you are passionate about AI-led transformation, enjoy whiteboarding with CXOs, and have the delivery scars that make your architectures and estimates credible - this role is for you.

•         Solution Design & Architecture: Architect end-to-end AI/ML, GenAI and Agentic AI solutions on AWS and Azure (GCP a plus), covering data pipelines, model training/fine-tuning, RAG and agent workflows, inference infrastructure, integration layers, security, observability and cost (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 - architecture documents, delivery approach, realistic effort and team estimates, assumptions, risks and SOW scoping.

•         Proof of Concept & Pilots: Define success criteria and build/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 - validate feasibility and estimates with delivery teams, run structured handover reviews, and stay engaged post-signoff to protect architectural integrity, resolve escalations and support customer acceptance on key engagements.

•         Customer Advisory: Act as a trusted AI advisor - run AI readiness and data maturity assessments, map business goals to AI roadmaps, identify quick wins, and propose 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 (AWS, Microsoft, etc.,).

•         Market Intelligence: Track AI platform and ecosystem updates (AWS, Azure, GCP, NVIDIA, open-source LLMs, agent frameworks) and proactively bring relevant innovations into customer conversations.

•         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 / Technical Lead on cloud, AI/ML projects - having owned technical delivery, managed scope, risks and customer expectations, and taken solutions from design to production.

•         Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, Step Functions, S3, Glue, etc.) or Azure AI/ML services (Azure AI Foundry, Azure ML, Data Factory, etc.).

•         Strong working knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, evaluation, and AI agent frameworks (LangChain, LlamaIndex, AutoGen, etc.).

•         Ability to architect end-to-end data and AI pipelines - from ingestion and processing to model serving, monitoring and cost optimisation - with sound judgement on build-vs-buy and scalability trade-offs.

•         Demonstrated experience leading RFP responses, solution proposals and architecture documents, including effort estimation and commercial inputs.

•         Working knowledge of MLOps / LLMOps lifecycle: model versioning, CI/CD for ML, monitoring, drift detection and guardrails.

•         Strong communication and stakeholder management skills - able to present confidently to both technical architects and business executives, and to lead customer workshops independently.

•         Experience mentoring or guiding junior architects and collaborating across Sales, Delivery and Partner teams.

•         Bachelor’s degree in Computer Science, Engineering or a related field; advanced degree is a plus.

•         AWS Certified Solutions Architect (Associate or Professional), AWS Certified Machine Learning Specialty, or equivalent Azure certifications.

•         Exposure to EdgeAI, VisionAI or Physical AI use cases in Manufacturing, Retail or Logistics.

•         Experience with NVIDIA platforms (NIM, NeMo, Jetson) or similar silicon-layer AI deployment tools.

•         Knowledge of Sovereign Cloud requirements and data residency regulations.

•         Familiarity with open-source LLMs (Mistral, LLaMA, Falcon) and their fine-tuning / deployment pipelines.

•         Understanding of enterprise data governance, security architecture and compliance frameworks.

•         Experience with Agile delivery, project governance and Agentic AI interoperability patterns (e.g., MCP, A2A).

•         Prior experience working in a cloud consulting or system integrator environment.