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AI Presales Engineer

  • AI Presales Engineer job type Posted on: Nov 01, 2026
  • AI Presales Engineer experience level CEI
  • AI Presales Engineer employment type Pittsburgh, Pennsylvania
  • AI Presales Engineer employment type Onsite
  • AI Presales Engineer salary Full-time

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Job Title :

AI Presales Engineer

Job Type :

Full-Time

Job Location :

Pittsburgh Pennsylvania United States

Remote :

No

Jobcon Logo Job Description :

PreSales, AI Engineering & Transformation – Job DescriptionRole OverviewThe Presales AI Engineer is a hybrid technical + consultative sales role responsible for helping clients understand, evaluate, and adopt AI-driven solutions. This role operates at the intersection of solution architecture, client engagement, and revenue generation, supporting the sales team in winning complex AI and digital transformation deals.You will partner with sales leaders, solution architects, and delivery teams to translate business challenges into AI solutions, develop demos and proof-of-value (PoV) engagements, and drive technical win strategy across enterprise opportunities.Primary ObjectivesAccelerate pipeline conversion and deal closure through strong technical solutioningEstablish credibility with enterprise clients as a trusted AI advisorDemonstrate business value of AI solutions through PoVs, demos, and architectureEnsure seamless transition from sales → deliveryKey Responsibilities1. Client Engagement & SolutioningPartner with sales teams in client meetings, discovery sessions, and executive briefingsTranslate business problems into AI/ML, GenAI, and data platform solutionsArticulate business value, ROI, and technical feasibility of AI solutionsEngage with C-level and technical stakeholders to shape solution vision2. Technical Presales ExecutionDesign and deliver custom demos, prototypes, and AI solution walkthroughsLead Proof of Value (PoV) initiatives aligned to client use casesDevelop reference architectures leveraging:Cloud platforms (Azure, AWS, GCP)Data platforms (Databricks, Fabric, Snowflake)GenAI frameworks (LLMs, RAG, agents)📌 Internal alignment: Presales teams are expected to support demo environments, PoVs, and technical validation during GTM motions 3. Proposal & Deal SupportCollaborate on RFP/RFI responses, proposals, and solution documentsDefine:Solution architectureDelivery approachEffort estimates and assumptionsSupport pricing strategy with technical inputs and risk considerations4. Sales Enablement & Thought LeadershipEnable sales teams with:AI solution positioningDemo scripts and playbooksObjection handling strategiesContribute to AI offerings, accelerators, and reusable assetsStay current on AI trends, tools, and competitive landscape5. Sell–Deliver ContinuityRemain engaged post-sale to ensure:Smooth handoff to delivery teamsAlignment between proposal and executionProvide advisory support during early delivery phases📌 Internal alignment: CEI emphasizes continuity from presales to delivery to reduce execution risk Required QualificationsTechnical SkillsStrong background in:AI / Machine Learning / Generative AIData engineering or software developmentExperience with:Python, APIs, and modern development frameworksCloud platforms (Azure, AWS, or GCP)AI frameworks (LLMs, vector databases, orchestration tools)📌 Alignment: CEI AI engineers are expected to have hands-on experience building AI-driven solutions in cloud environments

Jobcon Logo Position Details

Posted:

Nov 01, 2026

Reference Number:

10440_4479415473

Employment:

Full-time

City:

Pittsburgh

Job Origin:

APPCAST_CPC

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PreSales, AI Engineering & Transformation – Job DescriptionRole OverviewThe Presales AI Engineer is a hybrid technical + consultative sales role responsible for helping clients understand, evaluate, and adopt AI-driven solutions. This role operates at the intersection of solution architecture, client engagement, and revenue generation, supporting the sales team in winning complex AI and digital transformation deals.You will partner with sales leaders, solution architects, and delivery teams to translate business challenges into AI solutions, develop demos and proof-of-value (PoV) engagements, and drive technical win strategy across enterprise opportunities.Primary ObjectivesAccelerate pipeline conversion and deal closure through strong technical solutioningEstablish credibility with enterprise clients as a trusted AI advisorDemonstrate business value of AI solutions through PoVs, demos, and architectureEnsure seamless transition from sales → deliveryKey Responsibilities1. Client Engagement & SolutioningPartner with sales teams in client meetings, discovery sessions, and executive briefingsTranslate business problems into AI/ML, GenAI, and data platform solutionsArticulate business value, ROI, and technical feasibility of AI solutionsEngage with C-level and technical stakeholders to shape solution vision2. Technical Presales ExecutionDesign and deliver custom demos, prototypes, and AI solution walkthroughsLead Proof of Value (PoV) initiatives aligned to client use casesDevelop reference architectures leveraging:Cloud platforms (Azure, AWS, GCP)Data platforms (Databricks, Fabric, Snowflake)GenAI frameworks (LLMs, RAG, agents)📌 Internal alignment: Presales teams are expected to support demo environments, PoVs, and technical validation during GTM motions 3. Proposal & Deal SupportCollaborate on RFP/RFI responses, proposals, and solution documentsDefine:Solution architectureDelivery approachEffort estimates and assumptionsSupport pricing strategy with technical inputs and risk considerations4. Sales Enablement & Thought LeadershipEnable sales teams with:AI solution positioningDemo scripts and playbooksObjection handling strategiesContribute to AI offerings, accelerators, and reusable assetsStay current on AI trends, tools, and competitive landscape5. Sell–Deliver ContinuityRemain engaged post-sale to ensure:Smooth handoff to delivery teamsAlignment between proposal and executionProvide advisory support during early delivery phases📌 Internal alignment: CEI emphasizes continuity from presales to delivery to reduce execution risk Required QualificationsTechnical SkillsStrong background in:AI / Machine Learning / Generative AIData engineering or software developmentExperience with:Python, APIs, and modern development frameworksCloud platforms (Azure, AWS, or GCP)AI frameworks (LLMs, vector databases, orchestration tools)📌 Alignment: CEI AI engineers are expected to have hands-on experience building AI-driven solutions in cloud environments

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