Solution Architect

About The Role As an AI Solution Architect at Leena AI, you will own the technical and functional blueprint for enterprise AI deployments - translating customer business problems into scalable AI agent solutions built on our low-code/no-code platform. You'll sit at the intersection of client-facing solutioning and hands-on solution design: leading discovery, architecting the solution, configuring AI assistants and agentic workflows, and guiding implementation teams through delivery. This is not an infrastructure or cloud-ops role - it's a design, configuration, and client-advisory role for someone who thinks in prompts, workflows, integrations, and business outcomes rather than servers and pipelines.

Key Responsibilities

Solution Design & Architecture

• Lead discovery workshops and technical design sessions with enterprise stakeholders to understand business processes across HR, IT, Finance, and Enterprise Operations
• Translate business requirements into end-to-end AI agent solution designs — conversation flows, workflow automations, and integration architecture
• Architect and document solution blueprints, data flows, and configuration specs that implementation teams can build against
• Own the technical narrative in client conversations — presenting solution designs, defending architectural choices, and adjusting scope with stakeholders in real time

AI, LLM & Agent Configuration

• Design and configure AI assistants and agentic workflows using Leena AI's low-code/no-code platform - prompt design, tool/agent orchestration, and guardrails
• Customize LLM-powered experiences for customer-specific use cases, balancing accuracy, latency, and cost
• Configure multi-step agent workflows (approvals, escalations, human-in-the-loop) using in-house no-code/low-code tooling rather than custom backend builds
• Continuously refine prompts, knowledge sources, and agent logic based on evaluation results and production feedback

Enterprise Integrations & Delivery Oversight

• Design integration architecture with enterprise systems (Workday, ServiceNow, SAP, Oracle, UKG, SuccessFactors, Microsoft Entra ID/AD, Teams, Slack, Salesforce, Jira, Zendesk) using REST/GraphQL APIs, Webhooks, OAuth 2.0/OIDC, SAML 2.0, and SCIM
• Drive UAT, go-live readiness, and hypercare, resolving design-level issues that surface during rollout
• Identify solution risks (scope, integration, adoption) early and propose mitigations

Technical Leadership & Client Advisory

• Act as the senior technical point of contact for strategic accounts and complex, multi-system implementations
• Support pre-sales solutioning - scoping feasibility, effort, and architecture for prospective deployments
• Mentor on solution design practices, agent architecture patterns, and platform best practices.
• Build reusable solution templates, agent design patterns, and implementation accelerators to speed up future rollouts
• Stay current on LLM, RAG, and agentic AI developments and bring relevant patterns into customer solutions.
• Drive team performance and development - establish priorities, resolve technical bottlenecks, and lead regular design and code reviews for Solution Consultants and FDEs.
• Guide complex engagements hands-on - partner with team members throughout discovery and configuration to sharpen their solutioning capabilities, maintaining ultimate accountability for execution quality.

Required Qualifications

• B.Tech in Computer Science / Information Technology from a Tier 1 or Tier 2 Engineering college or Software Engineering background preferred.
• 6+ years of experience in solution consulting, implementation, or technical architecture within enterprise SaaS, with 2+ years designing AI/LLM-powered or conversational AI solutions
• Hands-on experience with LLM applications — prompt engineering, RAG, AI agents, tool calling, and evaluation/guardrails
• Proven experience designing and configuring solutions on workflow builders, conversation designers, automation tools.
• Strong client-facing track record: leading discovery workshops, presenting architecture to senior stakeholders, and managing scope conversations
• Working knowledge of enterprise integration patterns - REST/GraphQL APIs, Webhooks, OAuth 2.0/OIDC, SAML 2.0, SCIM and enterprise systems such as Workday, ServiceNow, SAP, or Oracle etc.
• Excellent communication, documentation, and stakeholder management skills
• Experience with AI frameworks/ecosystems such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar (as a consumer/configurer, not necessarily a framework-level builder)
• Familiarity with MCP (Model Context Protocol), multi-agent systems, and AI orchestration patterns
• Experience leading solutioning for large, multi-stakeholder enterprise implementations.

Skills: llm,solution architect,forward deployed engineering