Role description
Icertis- As the Technology Director - Solution Advisory, you will be at the forefront of our solution engineering efforts, shaping the future of contract lifecycle management (CLM) with AI integration
- Your role is pivotal in translating complex technical capabilities into tangible business solutions for our global clientele
- You will collaborate closely with C-suite executives, understanding their unique challenges and crafting innovative strategies to address them
- ▸ Lead and own end-to-end pre-sales engagements for enterprise CLM deals, from discovery to proof-of-concept to proposal
- ▸ Design compelling, tailored solution architectures that address complex procurement, legal, and commercial contracting challenges
- ▸ Build and deliver executive-level business cases, demonstrating quantifiable ROI of AI-powered contract intelligence
- ▸ Deliver live demos and POCs of Icertis ICI and its AI Copilot capabilities to audiences ranging from IT teams to CXOs
- ▸ Articulate Icertis’ Generative AI and LLM-based capabilities — including automated clause recommendations, contract risk scoring, and obligation tracking — to both technical and business stakeholders
- ▸ Position AI-native CLM features competitively, staying ahead of market trends in contract intelligence and legal tech
- ▸ Guide customers on AI governance, responsible AI adoption, and data privacy considerations in enterprise deployments
- ▸ Leverage agentic AI frameworks to illustrate how autonomous workflows can transform procurement and contracting operations
- ▸ Design and present integration architectures connecting ICI with CRM (Salesforce), ERP (SAP, Oracle), and middleware platforms such as Boomi and MuleSoft
- ▸ Lead technical conversations on Microsoft Azure cloud deployments, including Azure Commercial and Azure Government Cloud environments
- ▸ Advise on Azure AI Services integration — including Azure OpenAI, AI Search, and Document Intelligence — to enhance platform capabilities
- ▸ Engage with data platform discussions involving Snowflake, Databricks, and Microsoft Fabric in the context of AI and analytics use cases
- ▸ Engage confidently with diverse audiences — from business users and procurement leads to CTOs, CPOs, CLOs, and CFOs
- ▸ Collaborate with product, engineering, and customer success teams to relay field insights and influence the product roadmap
- ▸ Partner with regional sales teams across geographically distributed environments to drive pipeline and accelerate deal velocity
- ▸ Mentor junior solution engineers and contribute to the continuous development of pre-sales best practices and enablement assets- ▸ Excellent presentation, written, and verbal communication skills — including live demo delivery and executive storytelling
- ▸ Strong proficiency in Microsoft Azure cloud offerings (Commercial and/or Government); hands-on exposure to Azure AI Services highly valued
- ▸ Ability to thrive under pressure, manage multiple concurrent engagements, and collaborate effectively across global, distributed teams
- ▸ Demonstrated expertise in designing enterprise solutions, crafting value propositions, and building executive-level business cases
- ▸ High-level knowledge of CRM (e.g., Salesforce) and ERP (e.g., SAP, Oracle) systems and their integration touchpoints
- ▸ 14+ years of industry experience, with a minimum of 5 years in a pre-sales or solution engineering capacity for enterprise software or SaaS products
- ▸ Proven ability to translate complex AI and technology capabilities into clear, compelling business outcomes for executive audiences
- ▸ Experience with enterprise integration platforms such as Boomi, MuleSoft, or similar; familiarity with API-first and event-driven architectures
- ▸ Familiarity or hands on with SAP Suite of systems will be an added advantage
- ▸ Hands-on familiarity with Generative AI, LLMs, and their enterprise applications (e.g., Azure OpenAI, Copilot, RAG architectures)
- ▸ Understanding of AI/ML concepts — NLP, document classification, semantic search, predictive analytics — as applied to enterprise workflows
- ▸ Domain experience in procurement, sourcing, legal operations, or sales contracting; CLM platform knowledge is a significant advantage
- ▸ Working knowledge of data platforms such as Snowflake, Databricks, or Microsoft Fabric in AI/analytics contexts
- ▸ Familiarity with AI governance, responsible AI frameworks, and enterprise data privacy regulations (GDPR, CCPA, etc.)
- ▸ Background in contract lifecycle management, legal tech, or enterprise compliance technology