This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Success Engineer based in India.
This role is a high-impact customer-facing technical position focused on driving successful adoption and real-world value from advanced AI solutions across enterprise clients. The AI Success Engineer acts as the primary post-sales technical partner, guiding organizations through deployment, integration, and scale-up of AI capabilities into their core workflows. The role blends deep technical expertise with customer advisory, program leadership, and product enablement responsibilities. You will work closely with stakeholders ranging from engineering teams to executive sponsors to translate business objectives into actionable AI adoption roadmaps. This position sits at the intersection of technology and business transformation, ensuring customers realize measurable impact from AI implementations. It requires strong ownership, structured execution, and the ability to operate in fast-moving, complex enterprise environments.
Accountabilities:
- Lead post-sales technical engagements as the primary point of contact for enterprise customers adopting AI solutions.
- Drive customer onboarding, configuration, integration, and end-to-end deployment of AI products and APIs.
- Identify, validate, and prioritize high-impact AI use cases by embedding within customer workflows and understanding business challenges.
- Translate customer objectives into structured adoption roadmaps with clear milestones, KPIs, and success metrics.
- Manage multi-workstream delivery across technical implementation, change management, and product activation initiatives.
- Act as a liaison between customers and internal teams including product, engineering, solutions architecture, and research.
- Facilitate technical enablement sessions, workshops, and training to accelerate adoption and internal capability building.
- Track account health, adoption velocity, and value realization through structured reporting and performance metrics.
- Gather customer feedback and surface technical blockers or product insights to internal teams for continuous improvement.
- Support expansion opportunities by identifying new AI-driven workflows and additional use cases within existing accounts.
- Guide customers in measuring impact through baselines, KPI definition, and post-deployment analysis.
Requirements:
- 8+ years of experience in technical, customer-facing roles such as technical account management, solutions architecture, technical consulting, or enterprise SaaS delivery.
- Strong hands-on understanding of AI/ML concepts, including APIs, SDKs, embeddings, retrieval-augmented generation, and integration patterns.
- Experience working with large enterprise customers and managing complex, multi-stakeholder technical deployments.
- Ability to translate complex technical concepts into clear business value and strategic outcomes.
- Proven experience in driving adoption, onboarding, and long-term success of technical products or platforms.
- Strong program and project management skills with the ability to manage multiple parallel workstreams.
- Experience collaborating closely with engineering, product, and data teams in fast-paced environments.
- Strong analytical and problem-solving skills with a focus on structured execution and outcome delivery.
- Excellent communication and stakeholder management skills, including executive-level interactions.
- High ownership mindset with the ability to operate independently in dynamic customer environments.
Benefits:
- Competitive compensation aligned with experience and industry standards.
- Opportunity to work on cutting-edge AI technologies deployed at global enterprise scale.
- High-impact role shaping how organizations adopt and operationalize AI in real business workflows.
- Remote and hybrid flexibility based on location and team requirements.
- Exposure to world-class engineering, product, and research teams in the AI ecosystem.
- Strong career growth opportunities in advanced AI deployment and enterprise transformation.
- Continuous learning environment focused on emerging AI technologies and enterprise innovation.
- Inclusive, global, and innovation-driven work culture.