Role: Solution Architect – AI for Enterprise Applications
Location: Hyderabad, India
Employment Type: Full-Time
Experience: 6–15 Years
About the Role
We are looking for an experienced Solution Architect – AI for Enterprise Applications to lead the design, solutioning, and technical architecture of next-generation AI applications for enterprise customers.
This role is ideal for someone who can combine AI expertise, enterprise architecture, and customer-facing solutioning to build scalable AI systems that help organizations search knowledge, analyze business data, and automate workflows using AI.
You will work closely with customers, sales teams, AI engineers, and product teams to design production-grade AI solutions powered by Generative AI, LLMs, RAG, AI Agents, NLP, and enterprise automation frameworks.
Job Responsibilities
- Lead end-to-end solution architecture and technical design for enterprise AI applications aligned with business objectives.
- Engage in customer discovery, presales discussions, workshops, technical demos, and solution presentations.
Understand enterprise workflows and design AI solutions across use cases such as:
- Enterprise Knowledge Search
- AI-Powered Business Intelligence & Analytics
- Conversational AI & Virtual Assistants
- AI Agents for Workflow Automation
- Customer Support & Contact Center Automation
- IT Operations Automation
- Design architectures enabling AI systems to search across enterprise knowledge repositories, analyze structured data, and execute business workflows.
- Architect AI applications using LLMs, Retrieval-Augmented Generation (RAG), vector databases, orchestration frameworks, and agent-based systems.
- Define integration architecture with enterprise platforms such as:
- Knowledge systems (Confluence, SharePoint, Outlook, Email)
- Workflow systems (Jira, ServiceNow, GitHub, CRM)
- Databases and data warehouses (Postgres, SQL, cloud data platforms)
- Lead Proof of Concepts (POCs) and technical feasibility studies for client engagements.
- Create architecture documents including system design, API specifications, data flows, security models, and deployment blueprints.
- Ensure enterprise-grade implementation with focus on scalability, security, governance, auditability, and observability.
- Collaborate with engineering and product teams during implementation to ensure architecture compliance and delivery success.
- Stay current with advancements in Generative AI, Agentic AI, AI infrastructure, and enterprise AI platforms.
Required Experience & Skills
- 6+ years of experience in Solution Architecture, Enterprise Architecture, Technical Consulting, or Presales Engineering.
- 3+ years of experience working on AI/ML, NLP, or Generative AI systems.
Strong understanding of enterprise application architecture including:
- APIs & microservices
- Distributed systems
- Cloud-native deployments
- Event-driven workflows
- Hands-on experience with AI technologies such as:
- Large Language Models (LLMs)
- Prompt Engineering
- RAG pipelines
- AI Agent frameworks
- Vector Databases
- NLP / Speech AI
Strong understanding of AI deployment lifecycle including:
- Model serving
- Inference optimization
- MLOps / LLMOps
- Monitoring & observability
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Strong ability to translate business problems into scalable AI architectures.
- Excellent communication and presentation skills with customer-facing experience.
Preferred Qualifications
- Experience designing AI-powered enterprise copilots or AI agents.
- Exposure to enterprise integrations across CRM, ITSM, ERP, and support systems.
- Experience in industries such as BFSI, Enterprise SaaS, Telecom, Retail, Manufacturing, or IT Services.
- Familiarity with AI governance, access control, compliance, and enterprise security requirements.
- Startup experience or experience working in fast-paced product environments is a plus.
What We’re Looking For
We need someone who can think beyond models and build real enterprise AI applications—systems that can intelligently search, analyze, reason, and act across business workflows.
The ideal candidate is equally comfortable speaking to CXOs in boardrooms and engineers in architecture reviews.