Staff AI Customer Engineer

About The Role

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.

Responsibilities

• 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.

Requirements

• 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.

Qualifications

• 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 service line teams up for successful scaled implementation.
• High Agency – Ability to navigate ambiguity, operate autonomously, and represent Cognizant at the highest level in client environments.
• Experience in a specific enterprise vertical; background in AI consulting, technical advisory, or professional services
• Technical Skills & Tools: Languages & Engineering - Strong production coding across Python and at least one additional language; fluency in enterprise integration patterns. AI/ML & GenAI - Deep production expertise in LLMs, agentic architectures, evaluation frameworks, and MLOps/LLMOps at scale. Cloud Platforms - Multi-hyperscaler depth across AWS Bedrock, Google Vertex AI, and Azure AI Foundry; owns model selection, routing, open-weight self-hosting, and cost/latency optimization. Agent & Orchestration Frameworks - Designs multi-agent and stateful agent systems; selects among LangGraph, CrewAI, Microsoft Agent Framework, and vendor SDKs based on control, latency, and cost trade-offs; applies orchestration patterns (supervisor/worker, human-in-the-loop checkpoints). RAG & Retrieval - Designs enterprise retrieval architectures; evaluates vector store and indexing trade-offs for accuracy, scale, and cost. LLMOps — Eval & Observability - Establishes the evaluation and observability strategy for an engagement (LangSmith, Langfuse, Arize Phoenix, or Braintrust), including self-hosted options for data-residency requirements. Responsible AI & Governance - Embeds Responsible AI by design — model risk, safety, and bias controls — aligned to NIST AI RMF, ISO 42001, and the EU AI Act; applies sector compliance (SOC 2, HIPAA, PCI) as relevant. Practice Contribution - Codifies reusable patterns, accelerators, and reference implementations that build team IP.

Skills

• Strong production coding across Python and at least one additional language;
• Deep production expertise in LLMs, agentic architectures, evaluation frameworks, and MLOps/LLMOps at scale;
• Multi-hyperscaler depth across AWS Bedrock, Google Vertex AI, and Azure AI Foundry;
• Designs multi-agent and stateful agent systems;
• Selects among LangGraph, CrewAI, Microsoft Agent Framework, and vendor SDKs based on control, latency, and cost trade-offs;
• Establishes the evaluation and observability strategy for an engagement (LangSmith, Langfuse, Arize Phoenix, or Braintrust), including self-hosted options for data-residency requirements;
• Embeds Responsible AI by design — model risk, safety, and bias controls — aligned to NIST AI RMF, ISO 42001, and the EU AI Act;
• Codifies reusable patterns, accelerators, and reference implementations that build team IP.

Benefits

• The annual salary for this position is between $130,000-$230,000 depending on experience and other qualifications of the successful candidate.
• This position is also eligible for Cognizant’s discretionary annual incentive program and stock awards, based on performance and subject to the terms of Cognizant’s applicable plans.
• Cognizant offers the following benefits for this position, subject to apply:
• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Disclaimer

The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, based on applicable law.