5 days ago
Dallas, TX, USASenior
Responsibilities
- Design scalable, modular generative AI architectures for production use.
- Integrate GenAI capabilities into customer-facing and internal products and translate product requirements into AI-driven technical designs.
- Develop RAG architectures, vector database integrations, multi-agent systems, workflow orchestration, model routing, and fallback strategies.
- Support data and knowledge engineering, including data pipelines, feature engineering, unstructured data processing, knowledge graphs, metadata-driven architectures, and document ingestion.
- Implement MLOps capabilities on GCP, including model versioning, deployment pipelines, monitoring, logging, and drift detection.
- Address inference optimization, latency, cost control, AI security risks, guardrails, content filters, policy enforcement, responsible AI, privacy, and governance.
Requirements
- Strong understanding of generative AI models, LLMs, multimodal models, embeddings, and foundation models such as GPT-style, Claude-style, and LLaMA-style models.
- Hands-on experience with model adaptation, prompt engineering, prompt orchestration, agent-based frameworks, and machine learning fundamentals.
- Experience designing scalable AI architectures using RAG, vector databases, semantic search, embeddings indexing, multi-agent systems, and workflow orchestration.
- Experience integrating GenAI into products, including familiarity with A/B testing, feature flags, and iterative AI product releases.
- Proficiency in data pipelines, feature engineering, unstructured data processing, knowledge graphs, metadata-driven architectures, and document chunking strategies.
- Strong experience with cloud-native environments, particularly GCP, and familiarity with MLOps, containerization, Kubernetes, and CI/CD pipelines.
- Understanding of low-latency inference, model routing, fallback strategies, inference optimization, and cost-control strategies.
- Knowledge of prompt injection, data leakage, model abuse, guardrails, content filters, policy enforcement, explainability, bias mitigation, compliance, GDPR, and enterprise governance.
- Applicants must be legally authorized to work in the United States without requiring company sponsorship now or at any time in the future.
Benefits
- Remote work arrangement.
- Medical, dental, vision, and life insurance.
- 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 based on performance and applicable plan terms.
Tech Stack
Categories
About Cognizant
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value. We build full-stack AI solutions powered by deep industry, process and engineering expertise — embedding an organization's unique context into technology systems that amplify human potential and drive tangible outcomes. From strategy to deployment, we help global enterprises move from AI ambition to AI impact and stay ahead in a fast-changing world. See how at cognizant.ai | Follow us @cognizant