Lead Solutions Architect

Overview

Job Description

Platform, Integration & Customer Data Architecture

• Architect end-to-end platform, customer data, knowledge, and integration solutions leveraging Sprinklr’s connector ecosystem, unified customer intelligence frameworks, native import/export capabilities, knowledge systems, and REST API ecosystem.
• Design enterprise customer data architectures including customer identity resolution, profile unification, source-agnostic ingestion, structured/unstructured data harmonization, segmentation frameworks, consent and governance layers, customer memory, and omnichannel data continuity.
• Develop customer knowledge and experience architectures that activate operational, behavioral, conversational, and contextual customer intelligence across AI, service, marketing, and customer engagement workflows.
• Present enterprise architecture blueprints for common patterns — including CRM lifecycle integration, CDP synchronization, DAM connectivity, customer knowledge activation, omnichannel handover, case and interaction history continuity, reporting/analytics extraction, and platform extensibility.

AI, Agentic & Knowledge Leadership

• Lead AI, knowledge, and agentic solution design by mapping customer ecosystems to Sprinklr AI+, conversational AI, LLM ecosystems, enterprise search, RAG frameworks, NLP engines, memory architectures, and autonomous workflow orchestration.
• Define architectures for agentic enterprise use cases such as AI copilots, autonomous customer service agents, knowledge assistants, intelligent routing, AI-driven workflow execution, retrieval-augmented generation (RAG), customer memory systems, and real-time decision intelligence.
• Design knowledge governance frameworks including content ingestion, semantic search, taxonomy design, vectorization strategies, metadata structures, knowledge lifecycle management, and enterprise-safe AI deployment.
• Advise on AI + customer data governance including guardrails, hallucination mitigation, memory controls, observability, consent frameworks, model governance, and human-in-the-loop safety.

Presales Discovery, Consulting & Transformation

• Lead strategic discovery workshops to assess customer technology stacks, customer data maturity, AI readiness, and enterprise transformation opportunities across CRM, CDP, ERP, martech, DAM, analytics, cloud, compliance, and AI ecosystems.
• Map customer current-state ecosystems into Sprinklr’s unified platform, customer data, knowledge, and AI architecture while producing fit-gap analyses, phased transformation strategies, and extensibility roadmaps.
• Develop and deliver compelling technical demonstrations, AI showcases, and Proofs of Concept (POCs)highlighting customer data activation, bi-directional integration, knowledge orchestration, API-led extensibility, agentic AI, and unified customer experiences.
• Translate fragmented architectures into strategic business outcomes by identifying operational inefficiencies, customer experience gaps, AI opportunities, and transformation priorities.

Strategic Advisory & Thought Leadership

• Provide strategic guidance on enterprise architecture spanning authentication, customer identity, data governance, transformation pipelines, compliance, observability, rate management, knowledge governance, and AI safety.
• Collaborate across Sprinklr’s product, platform, AI, architecture, and sales ecosystem to validate designs against current capabilities and future roadmap priorities.
• Support RFPs, executive presentations, and technical strategy related to platform design, customer data architecture, AI transformation, knowledge governance, security, and compliance.
• Serve as a subject matter expert on Sprinklr’s platform + customer data + knowledge + AI + integration taxonomy, clearly articulating the value of unified architectures over fragmented ecosystems.
• Act as a trusted technical advisor to CIOs, Chief Digital Officers, Chief Data Officers, enterprise architects, AI leaders, and transformation teams by translating complex technical ecosystems into measurable business value.

Travel

• Travel up to 40% for customer engagements, strategic workshops, partner enablement, executive advisory sessions, and industry events.
• Who You Are & What Makes You Qualified

& Experience

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or related field; Master’s degree preferred.
• 7+ years of experience in enterprise platform architecture spanning integrations, customer data, AI, knowledge systems, or cloud ecosystems.
• 5+ years of experience architecting and demonstrating enterprise solutions in presales, solutions engineering, technical consulting, or transformation leadership roles with measurable revenue impact

Platform, Integration & Technical Depth

• Deep expertise in enterprise integration patterns including REST/GraphQL APIs, webhook orchestration, event-driven architecture, ETL/ELT pipelines, source-agnostic ingestion, identity systems, API gateways, and bi-directional SaaS connectivity.
• Hands-on experience with enterprise SaaS ecosystems including CRM, CDP, DAM, workforce management, analytics, martech, customer feedback, and operational systems.
• Strong proficiency with integration tooling and standards including OAuth 2.0, SAML/SSO, JSON/XML, iPaaS platforms, middleware, cloud integration ecosystems, and governance frameworks.

• Customer Data Architecture & Knowledge Systems

• Deep expertise in customer data architecture and enterprise knowledge design, including customer identity resolution, profile unification, master data alignment, metadata strategy, taxonomy design, knowledge graphs, and structured/unstructured data harmonization across CX, CRM, CDP, and service ecosystems.
• Proven experience architecting customer knowledge and experience frameworks that unify operational, behavioral, conversational, and contextual data to power personalized journeys, AI copilots, agentic workflows, retrieval-augmented generation (RAG), and enterprise search.
• Strong understanding of customer experience data models including journey orchestration, interaction history, case lifecycle, segmentation, consent, privacy, customer memory, and omnichannel continuity.
• Hands-on experience designing enterprise knowledge architectures supporting content governance, ingestion pipelines, semantic search, vectorization strategies, metadata frameworks, knowledge lifecycle management, and real-time decision intelligence.
• Ability to transform fragmented ecosystems into a unified customer data + knowledge + experience architecturethat improves customer outcomes, AI accuracy, operational efficiency, and platform scalability.

AI, Agentic & Data Intelligence

• Strong knowledge of AI/ML, Generative AI, and agentic architectures including LLMs, NLP, RAG, enterprise search, vector systems, orchestration frameworks, memory systems, autonomous agents, and intelligent workflow automation.
• Experience designing agentic systems with governance, observability, trust layers, guardrails, lifecycle management, and enterprise-safe deployment strategies.
• Familiarity with cloud data ecosystems such as Snowflake, Databricks, AWS, Azure, GCP, or equivalent enterprise data intelligence platforms.

Business Consulting & Leadership

• Strong capability to perform deep discovery across customer architecture, customer data maturity, AI readiness, and operational transformation needs while aligning phased adoption strategies.
• Excellent communication skills with the ability to influence enterprise architects, CIOs, CDOs, IT decision-makers, and C-suite executives by translating platform, data, AI, and customer experience architectures into business outcomes.
• Experience contributing to thought leadership, sales enablement, partner ecosystem growth, strategic transformation, and innovation programs.

Governance, Privacy & Security

• Strong knowledge of security, privacy, compliance, and responsible AI fr