15 Sep
|
Leena AI
|
Gurugram
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.
- Solid 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.
📌 Solution Architect (Gurugram)
🏢 Leena AI
📍 Gurugram