AI Customer Engineer at Cognizant

Teaneck, New Jersey, United States -

Full Time

Start Date

Immediate

Expiry Date

07 May, 26

Salary

0.0

Posted On

06 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Solution Architecture, Pre-sales, Technical Consulting, GenAI, LLMs, ML Engineering, Enterprise Integration, Collaboration, Stakeholder Management, Communication, Ideation Workshops, Proposal Development, Risk Assessment, Client Engagement, Technical Validation

Industry

IT Services and IT Consulting

Description

Artificial Intelligence Customer Engineer Location: US Reports to: SVP, AI Business & Design Leader Function: AI Sales Engineering / AI Business & Design About the Role We are looking for a highly skilled and consultative AI Senior Sales Customer Engineer to help clients understand, shape, and activate the potential of AI in their business. This role partners closely with sales, industry specialists, engineering, and clients to turn priority AI use cases into MVPs, POCs, and commercially strong solutions that accelerate deal conversion. You will sit at the intersection of AI technology, solution architecture, and business value, guiding clients from early‑stage ideation through to validated solution designs. This is a hands‑on, high‑impact role suited for a technical expert who thrives in ambiguous, fast‑moving sales cycles. Key Responsibilities 1. Discovery, Ideation & Art‑of‑the‑Possible Drive early‑stage discovery sessions with clients and account teams. Identify pain points, value levers, and high‑impact AI opportunities. Build “North Star” AI scenarios that illustrate meaningful business transformation. Translate vague or complex client questions into clear solution hypotheses and initial architectural logic. 2. Solution Shaping & Architecture Define end‑to‑end AI solution architectures, including LLM components, data/ML layers, integrations, and partner technologies. Create multiple solution pathways (good/better/best) with documented trade-offs. Conduct feasibility assessments, risk evaluations, and level‑of‑effort estimates. 3. Proposal Development & Client Engagement Create compelling, client‑ready content: SoWs, proposals, architecture decks, value frameworks, and demo storylines. Lead technical walkthroughs, deep‑dives, and competitive differentiation discussions. Refine solution narratives based on client feedback and market conditions. 4. Pursuit Orchestration & Cross‑Functional Collaboration Lead pursuit pods across Sales, Industry SMEs, AI Engineering, and Ecosystem Partners. Integrate hyperscale and partner inputs into solution design and positioning. Ensure solution readiness for delivery, including governance, risk alignment, and assumption tracking. Oversee seamless transition from sales to delivery, ensuring continuity and clarity. Decision Rights & Influence Owns Architecture design for high‑value AI use cases. Deal‑level solution shaping, feasibility, risk assessment, and documentation. Technical validation for proposals and Statements of Work. Influences Deal strategy, competitive positioning, and proposal direction. Prioritization of engineering and partner support during pursuits. Partner selection and delivery model decisions. Key Performance Indicators Contribution to deal conversion and solution progression. Quality and competitiveness of solution designs. Accuracy of estimation, risk identification, and technical validation. Effectiveness of cross‑functional orchestration and client engagement. Stakeholders You Will Work With Internal Stakeholders AI Sales Specialists Industry/Domain Specialists AI Engineers & Data Architects AI Business & Design Delivery & Engagement Teams Business Offerings & Pricing Teams Ecosystem & Alliance Teams External Stakeholders Client CIO, CTO, CDO, and Architecture teams Client Business Leaders (CX, Finance, Operations, Digital, etc.) Hyperscale’s, LLM providers, and ISVs for co‑sell and co‑build motions Experience Required 5+ years in AI/ML engineering, solution architecture, pre‑sales, or technical consulting. Strong expertise in GenAI, LLMs, agent architectures, ML engineering, and enterprise integration patterns. Experience leading ideation workshops and art‑of‑the‑possible sessions for technical and business stakeholders. Proven track record shaping AI deals, producing SoWs/proposals, and designing POCs or MVPs. Hands‑on experience building prototypes during sales cycles. Strong collaboration, stakeholder management, and communication skills. Key Competencies Ideation & Conceptual Design — ability to stretch client thinking and identify value creation. Solutioning Excellence — architecting scalable, feasible, high‑value AI solutions. AI/ML Technical Depth — understanding of LLMs, data pipelines, MLOps, and agent‑based patterns. Commercial Acumen — ability to assess tradeoffs, pricing, scoping, and ROI. Cross‑Functional Leadership — leading multi‑team pursuits and integrating complex inputs. Client Storytelling — simplifying technical complexity for business and technical audiences. Risk & Governance Rigor — strong discipline in documenting assumptions and mitigating risks. Why This Role Matters As an AI Senior Sales Engineer, you directly influence the success of multi‑million‑dollar AI opportunities. You are the technical architect, the solution narrator, and the strategic advisor who turns possibilities into actionable, high‑impact solutions that help clients scale AI responsibly and effectively. This is a high‑visibility role with the opportunity to shape some of the most important AI deals in the Americas region.

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Responsibilities

The AI Customer Engineer will drive discovery sessions with clients to identify AI opportunities and shape solutions. They will also lead cross-functional collaboration to ensure solution readiness and oversee the transition from sales to delivery.