AI Customer Engineer
Listed on 2026-06-19
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Software Development
AI Engineer (Applied/Software)
Staff AI Customer Engineer
As a Staff AI Customer Engineer, you will make an impact by leading client discovery, shaping AI-driven solutions, and delivering enterprise-grade generative AI outcomes that drive measurable business value. You will collaborate with senior stakeholders and cross‑functional teams to bring AI solutions from concept to production.
In this role, you will:- Lead early‑stage discovery and art‑of‑the‑possible ideation sessions engaging CxO and senior executive audiences with authority and confidence to frame high‑value AI opportunities.
- Embed with strategic clients to build production‑ready AI applications owning the end‑to‑end engineering lifecycle from prototype through deployment.
- Shape end‑to‑end AI solution architectures defining agentic platforms, data pipelines, ML components, integration patterns, and partner technologies.
- Build and sustain trusted executive relationships serving as the senior client‑facing voice throughout the engagement lifecycle and proactively identifying new AI opportunities as they emerge.
- Partner with clients throughout the MVP build cycle managing executive‑level expectations, communicating progress with clarity and poise, enabling client teams, and ensuring a comprehensive, well‑documented handoff to delivery and service line teams for scaled implementation.
- Develop and present client‑ready solution artifacts including proposals, Statements of Work, architecture decks, and executive narratives that make complex AI accessible to senior business audiences.
- Apply architecture decisions that balance quality, safety, latency, cost, and model risk establishing reusable deployment patterns that benefit the broader practice.
- Orchestrate cross‑functional pursuit teams across sales, engineering, delivery, and ecosystem partners ensuring consistent, differentiated outcomes for clients.
- Identify and codify repeatable deployment patterns contributing insights back to product, engineering, and practice leadership.
- Mentor and develop junior engineers through deal reviews, coaching, and development planning.
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 2-3 days a week in a client or Cognizant office. Regardless of your working arrangement, we are here to support a healthy work‑life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered- Experience: 8+ years in AI/ML engineering, solution architecture, pre‑sales, or technical consulting.
- Executive Presence: Proven ability to engage C‑suite and senior business executives with authority, composure, and influence; commanding credibility in high‑stakes client settings.
- Production Delivery: Demonstrated success deploying GenAI‑powered solutions in client or enterprise environments at scale.
- Discovery & Solutioning: Proven ability to lead structured discovery, ideation workshops, and solution design for complex AI opportunities.
- Client Relationship Management: Track record of building and sustaining senior executive relationships and growing account presence over the engagement lifecycle.
- Executive Presence & Credibility – Commanding trust and authority in C‑suite and senior executive settings; navigating complex organizational dynamics and influencing key decisions with confidence and composure.
- Ideation & Art‑of‑the‑Possible – Guiding senior client leaders toward transformative AI scenarios and measurable business value creation.
- Solutioning Excellence – Designing scalable, feasible, and differentiated AI solutions across diverse industry contexts.
- AI/ML Technical Depth – Comprehensive mastery of GenAI, LLMs, ML engineering, data pipelines, and agentic architectures in production environments.
- Handoff & Continuity – Ensuring MVP‑to‑delivery transitions are thorough, well‑documented, and set…
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