• Partner with Sales to qualify opportunities, understand customer challenges, and shape solution strategies aligned to business outcomes. • Lead discovery sessions focused on workflows, operating models, and tooling across IT, engineering, and business teams. • Design and deliver tailored demonstrations and solution narratives across Atlassian platforms (Jira, Confluence, Jira Service Management, etc.). • Translate customer needs into scalable solution architectures spanning Agile delivery, ITSM, and enterprise work management. • Articulate the value of modern ways of working: connecting portfolio management, DevOps, and service management into a cohesive story. • Provide technical validation and guidance throughout the sales cycle, ensuring solutions are feasible, scalable, and aligned to best practices. • Collaborate closely with delivery teams to ensure continuity from presales to implementation. • Contribute to RFP/RFI responses with clear, structured solution approaches and supporting technical detail. • Stay current on Atlassian capabilities, marketplace ecosystem, and evolving trends in work management and service delivery.

• Act as a go-to expert for AI-related topics across client engagements. • Lead the design of end-to-end AI architectures, including data pipelines, model training environments, integrations, and MLOps strategies. • Evaluate and select appropriate AI frameworks, tools, and models. • Support decision-making processes for make vs. buy AI solutions. • Ensure AI solutions comply with security standards, ethical guidelines, and enterprise reliability requirements. • Support product management and innovation teams in identifying AI use cases that deliver real business value (e.g. efficiency improvements, customer value). • Contribute to the creation of AI strategy and roadmaps, including ideation workshops, AI hackathons, and architecture discussions. • Provide technical leadership in Machine Learning, Generative AI, and Agentic AI. • Collaborate with product managers, data scientists, data engineers, and DevOps engineers to bring AI solutions into production. • Monitor and improve AI systems using performance metrics, A/B testing, and optimization techniques. • Research and evaluate emerging AI technologies and assess their impact on business transformation. • Drive knowledge sharing and AI adoption across the organization.

• Lead conversations with founders, operators, and team leads • Map out current workflows across departments (sales, ops, finance, marketing, etc.) • Identify bottlenecks, inefficiencies, and manual processes • Determine what can be automated, augmented with AI, eliminated or simplified • Produce a structured deliverable including current state workflow breakdown, identified automation opportunities, recommended solutions, implementation plan, and estimated impact • Translate roadmap into clear specs for engineering team • Provide light project oversight to ensure alignment with the original vision

• Comprehend customer billing frameworks and accurately configure contracts, pricing, metering, and invoicing. • Convert complex business needs into well-defined, organized workflows and configurations. • Develop solutions addressing intricate billing, revenue recognition, and reporting processes with a focus on desired results. • Collaborate with Sales for live demonstrations, sandbox configurations, and responses to RFPs. • Engage in discovery discussions with CTOs, CFOs, Controllers, VPs of Finance, and senior stakeholders to align customer requirements with Zenskar’s capabilities. • Create and maintain demo environments that accurately represent real-world enterprise scenarios. • Serve as the internal advocate for customers by providing structured insights to Product and Engineering teams. • Prepare clear documentation for smooth handoffs during deal or use case transitions. • Develop customer-specific solution documents and onboarding materials. • Contribute to internal knowledge repositories, enablement resources, and product documentation.