3 months ago
Base Salary
$130k - $230k/yr
Responsibilities
- Lead AI discovery and art-of-the-possible sessions with C-suite and senior executive audiences.
- Embed with strategic clients to build production-ready AI applications from prototype through deployment.
- Shape end-to-end AI architectures spanning agentic platforms, data pipelines, ML components, integrations, and partner technologies.
- Build executive relationships, identify new AI opportunities, and serve as the senior client-facing voice throughout engagements.
- Manage MVP build cycles, communicate progress, enable client teams, and deliver documented handoffs to delivery and service-line teams.
- Create proposals, Statements of Work, architecture decks, and executive narratives.
- Balance quality, safety, latency, cost, and model risk while establishing reusable deployment patterns.
- Orchestrate pursuit teams across sales, engineering, delivery, and ecosystem partners.
- Codify reusable patterns and contribute practice insights to product, engineering, and leadership teams.
- Mentor and develop junior engineers through coaching, deal reviews, and development planning.
Requirements
- 8+ years of experience in AI/ML engineering, solution architecture, pre-sales, or technical consulting.
- Proven ability to engage C-suite and senior business executives with authority, composure, and influence.
- Demonstrated success deploying GenAI-powered solutions in client or enterprise environments at scale.
- Experience leading structured discovery, ideation workshops, and solution design for complex AI opportunities.
- Track record of building and sustaining senior executive relationships and growing account presence.
- Deep production expertise in GenAI, LLMs, agentic architectures, evaluation frameworks, and MLOps/LLMOps.
- Strong production coding ability in Python and at least one additional language, with fluency in enterprise integration patterns.
- Multi-hyperscaler experience across AWS Bedrock, Google Vertex AI, and Azure AI Foundry, including model selection, routing, self-hosting, and cost/latency optimization.
- Experience designing multi-agent and stateful agent systems using appropriate orchestration frameworks and patterns.
- Experience designing enterprise retrieval architectures and evaluating vector-store and indexing trade-offs.
- Experience establishing LLM evaluation and observability strategies, including self-hosted options for data residency.
- Knowledge of responsible AI, model risk, safety, bias controls, NIST AI RMF, ISO 42001, EU AI Act, and applicable sector compliance.
- Background in an enterprise vertical, AI consulting, technical advisory, or professional services is helpful.
Benefits
- Hybrid work arrangement requiring 2–3 days per week in a client or Cognizant office, subject to project and business requirements.
- Medical, dental, vision, and life insurance, subject to eligibility.
- Paid holidays and paid time off.
- 401(k) plan and contributions.
- Long-term and short-term disability coverage.
- Paid parental leave.
- Employee Stock Purchase Plan.
- Eligibility for a discretionary annual incentive program and stock awards based on performance and applicable plan terms.
Tech Stack
Categories
Forward DeployedSolutions Engineering
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.