Sr. Director, AI Solutions

Location: California, India

Department: AI Solutions Engineering & Support

Experience: 15

• Rapid High-Fidelity Building: Directly leverage advanced AI coding tools (e.g., Cursor, Claude, v0, Copilot) to rapidly orchestrate, test, and spin up functional, high-fidelity solution prototypes from raw client telemetry.
• Accelerate Delivery Velocity: Collapse the distance between process discovery and working software by using conversational development to bypass standard engineering boilerplate, focusing your time on system logic, edge cases, and user experience.
• Enterprise Grade Vibe-coded apps: Use vibe-coded outputs to deploy production grade apps based on enterprise design patterns, security and best practices.
• Lead by Example: Serve as the internal evangelist for AI-augmented development, establishing best practices for how Skan's solutions engineering and PS teams can safely use AI code generation to build custom extensions without introducing technical debt.

• Establish Reference Architectures: Systematically audit custom customer builds to isolate repeatable telemetry, analytical, and agentic workflows. Design and evolve standard reference architectures and reusable patterns for Skan Intelligence and Skan Agents.
• Abstract Core Logic: Architect a rigid "Core vs. Extension" infrastructure for all framework products. Ensure the underlying analytical model is locked and deterministic, while allowing client-specific application stacks (ERPs, CRMs, core transactional systems) to be mapped via configuration metadata.
• Incorporate Advanced AI Capabilities: Embed native LLM primitives, stateful multi-agent interaction graphs (e.g., LangGraph), and advanced Retrieval-Augmented Generation (RAG) into the solution frameworks to handle complex, unstructured operational tasks.

• Lifecycle & Upkeep Management: Treat all solution frameworks as live software products. Manage their release roadmaps, feature backlogs, and continuous regression testing to guarantee complete compatibility as Skan’s core platform primitives evolve.
• Rigorous Release Engineering: Enforce software configuration discipline across the solution stack. Implement strict semantic version control (Git-based), branching strategies, and automated CI/CD packaging pipelines to deliver clean artifact updates to client environments.
• Platform Feedback Loop: Act as the strategic bridge back to the Core Product team. Advocate for new platform capabilities, APIs, or agent behaviors discovered during field deployments.

• Create Implementation Playbooks: Develop robust technical deployment blueprints, configuration guides, and troubleshooting runbooks for each productized solution framework.
• Upskill the Field: Lead technical enablement workshops and design certification paths to empower Skan's Professional Services organization, Solutions Engineers, and System Integrator (SI) partners to adopt, deploy, and customize frameworks autonomously.
• Govern Customizations: Review critical architecture decisions and field extensions to ensure custom client configurations adhere to strict platform standards without breaking base upgrade paths.

• Hire, develop, and inspire a growing team of AI and full-stack engineers, fostering a high-accountability culture focused on innovation, quality, and platform excellence.
• Collaborate and drive alignment across internal organizations — including Product, Infrastructure, and Go-to-Market — ensuring AI platform initiatives are well-integrated, business-relevant, and executed with a cohesive cross-functional strategy.
• Cultivate and manage third-party vendor partnerships, strategically leveraging external expertise and resources to complement internal capabilities, expand team capacity, and meet development milestones at pace.

• Experience: 10+ years of progressive software engineering or enterprise platform architecture experience, with a minimum of 3+ years strictly leading the design and deployment of GenAI, LLM-orchestration, or multi-agent networks in production.
• AI Tooling Mastery: Deep, demonstrable hands-on mastery of advanced AI coding environments (Cursor, Claude API, programming with LLMs) to build and deploy code at extreme velocity.
• Leadership & Influence: Proven track record as a technical leader and multiplier, with an innate ability to coach senior engineers and influence cross-functional Product, Engineering, and Security stakeholders without direct authority.
• AI & Data Primitives: Deep mastery of vector search engineering, Graph RAG, agent orchestration runtimes (e.g., LangGraph, AutoGen), and distributed event streaming.
• CI/CD & DevOps Discipline: Strong hands-on background in release management, infrastructure-as-code, prompt/config management, and building automated evaluation and observability frameworks (LLMOps).
• Domain Fluency: Excellent understanding of business process management (BPM), task-mining, or process-mining paradigms. Experience converting raw user activity data into structured technical roadmaps is critical.
• Executive Presence: Exceptional written and verbal communication skills, with a demonstrated ability to articulate complex technical trade-offs (latency, token unit economics, non-deterministic risks) to C-suite stakeholders and client IT governance boards.