AI Success Engineer
New
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years
- Required Skills
- RESTful APIsStakeholder management
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.
Responsibilities
- 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.
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