GCP AI Architect
Cognizant
- Location
- Dallas, TX
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 160,000–200,000/yr
Posted 16d ago
Job Summary
Core Generative AI & ML Expertise
- Strong understanding of Generative AI models (LLMs, multimodal models, embeddings).
- Hands-on experience with foundation models (e.g., GPT-style, Claude-style, LLaMA-style) and model adaptation techniques.
- Expertise in prompt engineering, prompt orchestration, and agent-based frameworks.
- Solid grounding in machine learning fundamentals, including supervised/unsupervised learning, evaluation metrics, and inference optimization.
AI Architecture & System Design
- Ability to design scalable, modular GenAI architectures for production use.
- Experience with:
- RAG (Retrieval-Augmented Generation) architectures
- Vector databases (semantic search, embeddings indexing)
- Multi-agent systems and workflow orchestration
- Strong understanding of low-latency inference, model routing, and fallback strategies.
- Knowledge of event-driven, microservices, and API-first architectures.
Product Engineering & Integration
- Experience integrating GenAI capabilities into customer-facing and internal products.
- Ability to translate product requirements into AI-driven capabilities and technical designs.
- Familiarity with A/B testing, feature flags, and iterative product releases involving AI.
Data & Knowledge Engineering
- Proficiency in data pipelines, feature engineering, and unstructured data processing.
- Experience with:
- Knowledge graphs
- Metadata-driven architectures
- Document ingestion and chunking strategies
- Strong understanding of data quality, provenance, and governance for AI systems.
Cloud, MLOps & Platform Skills
- Strong experience in cloud-native environments (GCP).
- Familiarity with MLOps practices, including:
- Model versioning
- Deployment pipelines
- Monitoring, logging, and drift detection
- Experience with containerization, Kubernetes, and CI/CD pipelines.
- Knowledge of inference optimization and cost-control strategies.
Security, Privacy & Responsible AI
- Understanding of AI security risks (prompt injection, data leakage, model abuse).
- Experience implementing guardrails, content filters, and policy enforcement.
- Knowledge of responsible AI practices, including explainability, bias mitigation, and compliance.
- Familiarity with data privacy regulations (e.g., GDPR, enterprise governance standards).
Salary and Other Compensation
The salary for this position is between $160,000 - $200,000k depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits
Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- 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, subject to applicable law.
Cognizant will only consider applicants for this position who are legally authorized to work in the United States without requiring company sponsorship now or at any time in the future.
Skills
- Generative AI
- LLMs
- Multimodal models
- Embeddings
- Foundation models
- GPT
- Claude
- LLaMA
- Prompt engineering
- Prompt orchestration
- Agent-based frameworks
- Machine learning
- Supervised learning
- Unsupervised learning
- Evaluation metrics
- Inference
- RAG
- Vector databases
- Semantic search
- Multi-agent systems
- Workflow orchestration
- Model routing
- Fallback strategies
- Event-driven architecture
- Microservices
- API-first
- A/B testing
- Feature flags
- Data pipelines
- Feature engineering
- Unstructured data processing
- Knowledge graphs
- Metadata-driven architectures
- Document ingestion
- Chunking
- Data quality
- Data governance
- GCP
- MLOps
- Model versioning
- Deployment pipelines
- Monitoring
- Logging
- Drift detection
- Containerization
- Kubernetes
- CI/CD
- Inference optimization
- Cost control
- AI security
- Prompt injection
- Data leakage
- Model abuse
- Guardrails
- Content filters
- Policy enforcement
- Responsible AI
- Explainability
- Bias mitigation
- Compliance
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