Sr. Consultant AI & Data Engineer (Data Engineering Skills + Gen-AI & ML-ops Experience)
Share
Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
The Senior Consultant - AI & Data Engineer is a highly skilled technical expert responsible for building enterprisegrade AI/ML solutions GenAI applications and scalable data engineering pipelines that enhance operational excellence across Visas Client Services organization. This role is fully handson and focuses on advanced engineering solution delivery and endtoend implementation of AIdriven data products.
The ideal candidate brings strong practical experience in AI engineering (34 years) combined with deep expertise in data engineering distributed systems and modern MLOps practices. This role does not require people management but demands strong individual technical leadership problemsolving capability and excellence in architecture coding and solution delivery.
Key Responsibilities
AI Engineering & GenAI Solutions:
- Design develop and deploy LLMbased applications retrievalaugmented generation (RAG) pipelines embeddingspowered search and NLP/ML models.
- Build GenAIdriven data products such as document intelligence systems knowledge assistants summarization services conversational interfaces and automated reasoning tools.
- Implement advanced AI engineering techniques including model finetuning prompt optimization vector indexing and scalable inference.
- Ensure AI systems comply with Visas standards for security reliability performance monitoring and responsible AI governance.
Data Engineering & Pipeline Development:
- Build and optimize scalable data pipelines ETL/ELT workflows and distributed processing systems to support AI/ML and analytics use cases.
- Develop highquality data models transformations and feature pipelines for production ML systems.
- Integrate structured and unstructured data sources from multiple internal and external systems into enterprise data platforms.
- Implement data quality lineage observability audit logging and metadata management for missioncritical datasets.
MLOps & Platform Engineering:
- Develop endtoend ML pipelines including model training evaluation deployment and monitoring using modern MLOps frameworks.
- Implement CI/CD workflows automated testing feature stores experiment tracking and scalable serving layers.
- Build containerized cloudnative AI services using Docker Kubernetes and serverless components.
- Optimize performance across GPU workloads vector retrieval systems and largescale batch/streaming jobs.
Technical Collaboration & Solution Delivery:
- Work closely with product owners architects data scientists and engineering teams to translate business requirements into robust technical designs.
- Participate in architecture reviews propose design improvements and guide best practices in coding data modeling and ML lifecycle management.
- Deliver welldocumented maintainable and secure production code.
- Troubleshoot complex AI pipeline and data performance issues in development staging and production environments.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications :
Required Qualifications:
89 years of experience in data engineering AI engineering or machine learning development roles.
34 years of strong handson experience building and deploying production AI/ML solutions.
Expertise in:
Python (including ML libraries) SQL distributed systems
AI/ML frameworks: PyTorch TensorFlow Scikit-learn and GenAI toolkits
Vector DBs and RAG stack: FAISS Milvus Elasticsearch
Data engineering tools: Spark Kafka Airflow Databricks or similar
Cloud platforms: AWS GCP or Azure
Containerization and orchestration: Docker Kubernetes
Proven ability to build:
GenAI data products (LLM apps knowledge retrieval chat interfaces)
Data pipelines powering ML and analytics
Scalable secure inference services
Strong knowledge of data modeling distributed computing and modern data architectures.
Skilled in CI/CD testing logging monitoring and engineering best practices for ML systems.
Ability to collaborate with crossfunctional teams gather requirements and deliver technical solutions independently.
Preferred Qualifications:
Experience with LLM finetuning embeddings optimization or domain adaptation techniques.
Familiarity with AI governance responsible AI and enterprise security/compliance standards.
Experience with feature stores experiment tracking and advanced MLOps frameworks.
Background in financial services payments or client operations environments.
Masters degree in Computer Science Engineering or related technical discipline.
Additional Information :
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race color religion sex national origin sexual orientation gender identity disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Remote Work :
No
Employment Type :
Full-time
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
Visa (NYSE: V) is a world leader in digital payments, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories. Our purpose is to uplift everyone, everywhere by being the best way to pay and b ... View more
