WorkNEXT AI Transformation Head
Role Summary
The WorkNEXT AI Tech Expert is the technical ambassador for WorkNEXT AI modules—owning end-to-end client engagement, discovery, solution design, demos, pilots, and technical enablement. This role translates business pain points into pragmatic AI solutions, drives adoption and outcomes, and partners with product, engineering, and customer success to ensure WorkNEXT deployments deliver measurable value at scale.
Key Responsibilities
Client Engagement & Solutioning
- Lead technical conversations with enterprise clients: discovery, requirements analysis, solution architecture, and value mapping.
- Conduct tailored demos and hands-on workshops for WorkNEXT AI modules (e.g., workflows, assistants, analytics, automation).
- Design proof-of-concepts (POCs) and pilot plans, including success criteria, data readiness, and deployment approach.
- Translate business needs into AI-driven use cases and solution designs (incl. integrations, data pipelines, governance).
Technical Ownership
- Build reference architectures and implementation playbooks for WorkNEXT AI modules across common enterprise stacks.
- Partner with engineering to scope features, validate feasibility, and drive technical issue resolution.
- Configure and optimize WorkNEXT AI models and workflows (prompt strategies, orchestration, guardrails, evaluation).
- Ensure compliance with security, privacy, and responsible AI standards; coordinate with InfoSec and legal teams.
Customer Success & Enablement
- Create client-facing technical collateral: solution briefs, runbooks, FAQs, architecture diagrams, ROI calculators.
- Train client admins and super-users; develop enablement plans and adoption campaigns.
- Monitor post-deployment health: performance metrics, drift, model evaluation, user feedback loops.
Cross-Functional Collaboration
- Capture client feedback and market signals to inform product roadmap and prioritization.
- Collaborate with Sales/Pre-Sales for deal strategy, estimates, and RFP responses.
- Work with Data Engineering and Integration teams to ensure robust pipelines and API/connector reliability.
Required Skills & Competencies
Technical
- Strong understanding of AI/ML foundations: NLP, LLMs, retrieval-augmented generation (RAG), prompt engineering, model evaluation.
- Experience with cloud platforms (Azure/AWS/GCP), containerization (Docker/Kubernetes), and API integration patterns (REST, GraphQL, webhooks).
- Knowledge of data pipelines (ETL/ELT), vector databases/embeddings, and observability of AI systems.
- Familiarity with enterprise security, compliance, and responsible AI (RBAC, PII handling, auditability, human-in-the-loop).
- Ability to create architecture diagrams, deployment runbooks, and performance monitoring strategies.
Client-Facing
- Exceptional communication—can simplify complex AI concepts for non-technical stakeholders.
- Consultative approach—discovery, problem framing, value story, and objection handling.
- Strong demo presence; comfortable tailoring demos to industry verticals and role personas.
- Negotiation and stakeholder management across business, IT, InfoSec, and procurement.
Mindset
- Outcome-oriented: focuses on measurable business impact, not just features.
- Curious and experimental: rapid prototyping, A/B testing, iterative improvement.
- Ownership and accountability: proactive risk management, transparent communication.
Qualifications
- 6–10+ years in Client-Facing Technical roles (e.g., Solutions Architect, Pre-Sales Engineer, AI Consultant).
- 3+ years hands-on with AI/ML, LLM applications, or automation platforms.
- Bachelor’s/Master’s in Computer Science, Data Science, Engineering, or equivalent experience.
- Experience in at least one enterprise vertical (e.g., BFSI, Manufacturing, Retail, Healthcare) is a plus.
- Certifications in cloud/AI (Azure AI Engineer, AWS ML Specialty, GCP ML Engineer) preferred.
Typical WorkNEXT AI Use-Case Areas (Adjust to your modules)
- Knowledge assistant with RAG for policy/SOP retrieval, multilingual Q&A.
- Process automation: ticket triage, claim summarization, email drafting, task routing.
- Insight generation: summarization of meetings/chats, trend analysis, risk alerts.
- Employee experience: HR policy assistant, IT helpdesk copilot, onboarding flows.
- Compliance & governance: redaction, PII detection, audit-ready conversation logs.
Tools & Tech Stack (Illustrative)
- Cloud & Infra: Azure (OpenAI, Cognitive Search), AWS (Bedrock, Sagemaker), GCP (Vertex AI).
- Data: Databricks/Snowflake/BigQuery; ETL tools (ADF, Airflow), vector stores (Pinecone, FAISS).
- Integration: REST/GraphQL APIs, iPaaS (MuleSoft, Boomi), event buses (Kafka).
- Observability & Evaluation: Prometheus/Grafana, MLflow, human eval tooling, prompt/version management.
- Security: OAuth2/OIDC, RBAC, KMS, DLP; Responsible AI guardrails & content filters.
Über Cognizant
Cognizant (NASDAQ: CTSH) i ist ein Technologiedienstleister und Entwickler von KI-Lösungen. Wir schlagen die Brücke zwischen KI-Investitionen und echtem unternehmerischem Mehrwert, indem wir ganzheitliche Full-Stack-KI-Lösungen für unsere Kunden entwickeln. Mit unserer fundierten Branchen-, Prozess- und Engineering-Expertise integrieren wir die spezifischen Anforderungen von Unternehmen passgenau in Technologiesysteme. So entfalten wir das menschliche Potenzial, erzielen greifbare Ergebnisse und sichern globalen Unternehmen in einer sich rasant wandelnden Welt den entscheidenden Vorsprung. Erfahren Sie mehr unter cognizant.ai oder @cognizant.
Zusätzliche Informationen zur Beschäftigung
Die Vergütungsinformationen sind zum Zeitpunkt der Veröffentlichung dieser Stellenausschreibung korrekt. Cognizant behält sich das Recht vor, diese Informationen jederzeit unter Beachtung der geltenden gesetzlichen Bestimmungen zu ändern.
Bewerberinnen und Bewerber können verpflichtet sein, an Vorstellungsgesprächen persönlich oder per Videokonferenz teilzunehmen. Darüber hinaus kann es erforderlich sein, bei jedem Gespräch einen gültigen staatlichen Lichtbildausweis vorzulegen.
Cognizant ist ein Arbeitgeber mit Chancengleichheit. Ihre Bewerbung und Kandidatur werden nicht aufgrund von Rasse, Hautfarbe, Geschlecht, Religion, Glaubensbekenntnis, sexueller Orientierung, Geschlechtsidentität, nationaler Herkunft, Behinderung, genetischen Informationen, Schwangerschaft, Veteranenstatus oder sonstiger durch bundes‑, landes‑ oder kommunalrechtliche Vorschriften geschützter Merkmale berücksichtigt oder abgelehnt.
