5 months ago
Chennai, IndiaStaff+
Responsibilities
- Lead technical client conversations including discovery, requirements analysis, solution architecture, and value mapping.
- Conduct tailored demonstrations and hands-on workshops for WorkNEXT AI modules.
- Design proof-of-concepts and pilot plans with success criteria, data-readiness assessments, and deployment approaches.
- Translate business needs into AI-driven use cases and solution designs involving integrations, data pipelines, and governance.
- Build reference architectures, implementation playbooks, deployment runbooks, architecture diagrams, solution briefs, FAQs, and ROI calculators.
- Configure and optimize AI models and workflows using prompt strategies, orchestration, guardrails, and evaluation.
- Partner with engineering to scope features, validate feasibility, and resolve technical issues.
- Ensure security, privacy, compliance, and responsible AI standards in coordination with InfoSec and legal teams.
- Train client administrators and super-users and develop enablement and adoption plans.
- Monitor post-deployment performance, drift, model evaluation results, and user feedback loops.
- Capture client feedback and market signals for product roadmap prioritization.
- Collaborate with sales and pre-sales on deal strategy, estimates, and RFP responses.
- Work with data engineering and integration teams on pipeline and API or connector reliability.
Requirements
- 6–10+ years of experience in client-facing technical roles such as Solutions Architect, Pre-Sales Engineer, or AI Consultant.
- At least 3 years of hands-on experience with AI/ML, LLM applications, or automation platforms.
- Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or equivalent experience.
- Strong understanding of NLP, LLMs, retrieval-augmented generation, prompt engineering, and model evaluation.
- Experience with cloud platforms, containerization, API integration patterns, data pipelines, vector databases, embeddings, and AI observability.
- Knowledge of enterprise security, compliance, responsible AI, RBAC, PII handling, auditability, and human-in-the-loop processes.
- Ability to create architecture diagrams, deployment runbooks, and performance-monitoring strategies.
- Exceptional communication, consultative discovery, value-storytelling, demonstration, negotiation, and stakeholder-management skills.
- Experience in an enterprise vertical such as BFSI, manufacturing, retail, or healthcare is preferred.
- Cloud or AI certifications such as Azure AI Engineer, AWS ML Specialty, or GCP ML Engineer are preferred.
Tech Stack
Apache AirflowApache KafkaAWSAzureDatabricksDockerGoogle BigQueryGoogle Cloud PlatformGrafanaGraphQLKubernetesMLflowPrometheusSnowflake
Categories
Solutions 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.