1 day ago
Base Salary
$88k - $135k/yr
Responsibilities
- Design, develop, and deploy production-grade AI and machine learning solutions.
- Build and maintain generative AI and agentic AI applications using multi-agent orchestration frameworks.
- Develop RAG and Natural Language-to-SQL applications.
- Create and optimize LLM evaluation, monitoring, observability, and governance frameworks.
- Design scalable NLP solutions for classification, semantic search, topic modeling, sentiment analysis, and embedding-based applications.
- Develop and deploy machine learning models using statistical and deep learning techniques.
- Build data pipelines and AI workflows using Python, PySpark, SQL, and cloud-native technologies.
- Implement MLOps practices including CI/CD, model validation, monitoring, drift detection, and automated quality controls.
- Collaborate with stakeholders, architects, data engineers, and business teams to deliver scalable AI solutions.
- Ensure AI systems meet enterprise governance, security, compliance, and responsible AI standards.
- Contribute to AI platform architecture, modernization initiatives, and continuous improvement.
Requirements
- Bachelor’s degree in computer science, data science, engineering, mathematics, or a related field.
- 8+ years of experience in machine learning, artificial intelligence, data science, or related disciplines.
- Strong hands-on experience developing and deploying enterprise AI/ML solutions in production environments.
- Experience with generative AI, RAG, agent-based systems, prompt engineering, and LLM evaluation.
- Expertise in Python and AI/ML libraries including PyTorch, TensorFlow, Scikit-Learn, and Hugging Face.
- Experience with LangGraph and/or LangChain for AI application development.
- Strong knowledge of NLP techniques including classification, semantic similarity, embeddings, clustering, and topic modeling.
- Experience designing scalable data pipelines using SQL and PySpark.
- Experience deploying solutions on AWS, Azure, or Google Cloud Platform.
- Knowledge of Docker and Kubernetes.
- Experience implementing MLOps practices including model deployment, monitoring, validation, CI/CD, and observability.
- Strong communication skills and ability to translate technical concepts into business value.
Benefits
- Remote position open to qualified applicants in the United States, subject to business, project, and client 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.
- Eligible for Cognizant’s discretionary annual incentive program based on performance and applicable plan terms.
Tech Stack
Categories
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.