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Forward Deployed Engineer
Guides enterprise customers through technical AI implementation journeys by serving as both strategic advisor and hands-on executor for complex AI solution deployments
Key Responsibilities:
- Guide customers through entire technical journey including pre-sales validation, solution architecture, implementation, and ongoing success
- Architect and implement generative AI applications using large language models, vector databases, and AI orchestration frameworks
- Lead complex data-oriented projects involving multiple stakeholders across enterprise data ecosystems and API integrations
- Identify and capture expansion opportunities in existing accounts through consultative technical engagements
- Translate complex technical concepts to various audiences while building trust-based relationships with technical and business stakeholders
- Travel onsite to customer engagements to provide hands-on implementation support and strategic guidance
- Work with data access technologies, query languages, and data transformation techniques at enterprise scale
Skills & Tools:
- Technical pre-sales and post-sales implementation experience (7+ years)
- Generative AI application design and implementation
- Large language models, vector databases, and AI orchestration frameworks
- Data access technologies and API development
- MLOps, DataOps, and AI engineering practices
- Enterprise data ecosystems and modern architecture patterns
- Query languages and data transformation techniques
- Complex stakeholder management and consultative engagement
- Strong communication and relationship-building abilities
- Travel flexibility for customer engagements
Where This Role Has Appeared:
- PromptQL (AI Data Platform, SF Bay Area/Remote, $180k-$250k+ OTE, July 2025)
Variants & Related Titles:
- Customer Solutions Engineer
- Technical Implementation Manager
- AI Solutions Architect
- Customer Engineering Lead
- Technical Customer Success Manager
Why This Role Is New:
Forward Deployed Engineer emerged in 2022-2024 as AI products became too complex for traditional sales engineering or customer success teams to handle. The role addresses the unique challenge that enterprise AI implementations require deep technical expertise, on-site presence, and ongoing strategic guidance that combines elements of consulting, engineering, and customer success in ways that didn't exist before AI became enterprise-critical.
Trend Insight:
As AI becomes core business infrastructure rather than experimental technology, companies are creating hybrid technical roles that can bridge the gap between sophisticated AI products and complex enterprise implementation requirements, ensuring customers achieve transformational results rather than just successful deployments.
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