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Sr. Consultant - AI & Data Engineer

Sr. Consultant - AI & Data Engineer

Visa

8 - 9 years

15 - 20 Lacs

bengaluru

Posted:1 hour ago| Platform:

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Skills Required

computer science data modeling coding solution delivery distribution system analytics monitoring sql python auditing

Work Mode

Work from Office

Job Type

Full Time

Job Description

Key Responsibilities

AI Engineering & GenAI Solutions:

Design, develop, and deploy LLM based applications, retrieval augmented generation (RAG) pipelines, embeddings powered search, and NLP/ML models.
Build GenAI driven data products such as document intelligence systems, knowledge assistants, summarization services, conversational interfaces, and automated reasoning tools.
Implement advanced AI engineering techniques including model fine tuning, prompt optimization, vector indexing, and scalable inference.
Ensure AI systems comply with Visa s 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 high quality 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 mission critical datasets.

MLOps & Platform Engineering:

Develop end to end 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, cloud native AI services using Docker, Kubernetes, and serverless components.
Optimize performance across GPU workloads, vector retrieval systems, and large scale 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 well documented, maintainable, and secure production code.
Troubleshoot complex AI, pipeline, and data performance issues in development, staging, and production environments.

Required Qualifications:
8-9+ years of experience in data engineering, AI engineering, or machine learning development roles. 3-4+ years of strong hands on 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 cross functional teams, gather requirements, and deliver technical solutions independently. Preferred Qualifications: Experience with LLM fine tuning, 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. Master s degree in Computer Science, Engineering, or related technical discipline.

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Sr. Consultant - AI & Data Engineer