Enterprise Sr. AI Solution Architect

Team: AI - Solutions Team (Pre-sales)

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

About the Role

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.

Key Responsibilities

• 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.

What We’re Looking For

• 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.

Good to Have

• 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.