Deployment Strategist

Accountabilities: Partner with sales and senior customer stakeholders to conduct deep discovery, understand organizational and technical landscapes, and identify high-value business problems. Quantify business value and translate customer challenges into clearly defined opportunities, pilots, and measurable outcomes. Define the Minimum Viable Product for customer engagements, including scope, success criteria, timelines, and delivery priorities. Own product direction throughout the engagement, acting as the bridge between business requirements and engineering execution. Author product requirements documents, user stories, acceptance criteria, and other specifications that provide clear direction to engineering teams. Prioritize engineering backlogs, manage scope, coordinate delivery, and act as a hands-on quality assurance partner throughout implementation. Translate business requirements into data, integration, security, operational, and technical requirements that engineering teams can execute against. Lead technical discovery and design discussions, working with engineers to evaluate architecture options and identify trade-offs. Develop a strong understanding of customer data flows, integrations, platform constraints, security requirements, and operating environments. Identify and mitigate technical, organizational, and delivery risks early, removing blockers that could prevent successful implementation. Lead agile delivery processes and coordinate stakeholders ranging from C-suite executives to individual engineers. Own production launch activities, including launch planning, war-room coordination, production readiness, and issue resolution. Drive post-launch adoption by gathering user feedback, iterating on the solution, and demonstrating progress against defined business outcomes. Ensure production readiness across data quality, testing, security, performance, reliability, and operational processes. Define maintenance and support approaches, create customer documentation and training materials, and facilitate effective handoffs. Build trusted-advisor relationships with customers and identify opportunities for future high-value engagements. Capture reusable solution patterns and field insights and communicate them back to Product and Engineering teams to inform future development. Requirements Typically 7+ years of experience delivering complex, customer-facing data, analytics, AI, or software engagements, or equivalent experience as a founder or technical builder. Demonstrated experience delivering data, machine learning, or generative AI systems into production and understanding the integration, operational, and adoption challenges involved. Strong product management capabilities, including problem definition, product requirements, prioritization, scope management, roadmap thinking, and agile delivery. Deep technical fluency across modern data and AI architectures, including cloud platforms, data pipelines, data models, distributed systems, APIs, security, governance, machine learning, and generative AI application patterns. Ability to lead architecture discussions, evaluate technical trade-offs, pressure-test proposed solutions, and identify architectural risks. Hands-on technical ability in at least one language such as Python, Java, or SQL. Comfortable exploring data, working in notebooks, reviewing code and data pipelines, developing or adapting prototypes, and contributing to technical troubleshooting. Strong understanding of how business requirements translate into technical, data, integration, security, and operational requirements. Exceptional executive presence and communication skills, with the ability to build credibility and trust with senior stakeholders. Ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Strong stakeholder-management, influencing, and negotiation skills, particularly in complex customer environments. Ability to work effectively in ambiguous, fast-moving situations and make sound decisions while balancing customer, technical, and business priorities. Experience working in a high-growth technology company, forward-deployed engineering organization, leading consultancy, or similarly complex delivery environment is advantageous. Willingness to work closely with customers onsite, typically around 25–50% of the time and potentially more depending on engagement requirements. Strong ownership mindset, with the ability to remain focused on measurable outcomes from initial discovery through production adoption. Benefits Opportunity to work on high-value, strategic data and AI engagements with significant customer impact. Direct exposure to C-suite stakeholders and complex enterprise business challenges. High degree of ownership across product definition, technical delivery, production launch, and customer adoption. Close collaboration with forward-deployed engineers and specialists across data, AI, cloud, and software engineering. Opportunity to work with modern data, machine learning, generative AI, and distributed systems architectures. Hands-on environment that combines product management, technical strategy, customer engagement, and delivery. Opportunity to develop reusable solution patterns and influence broader Product and Engineering direction. Remote working opportunity based in India, with customer travel as required. Comprehensive benefits and perks, with specific offerings determined by the applicable regional employment arrangement. Inclusive, collaborative environment focused on innovation, professional growth, and meaningful customer outcomes.