AI/ML Engineer: RAG & Agentic AI for Enterprise

Tata Consultancy Services Limited; Pennington (NJ); Sur place; USD 120 000 - 150 000; Plein temps

Résumé du poste

RAG Technologies is seeking experts to design and implement enterprise-scale GenAI applications using OpenAI, Claude, Gemini, Llama, and other models. You will build production-grade RAG architectures with vector search and semantic retrieval, and develop AI-powered apps with prompt engineering and memory management.

You will also optimize LLM performance, design hybrid AI architectures, and implement guardrails and compliance frameworks across banking and enterprise data environments.

Qualifications

• Experience designing enterprise-scale GenAI applications.
• Experience with vector search and semantic retrieval.
• Experience with prompt engineering and memory management.
• Experience with production-grade AI pipelines.
• Familiarity with guardrails and compliance frameworks.

Responsabilités

• Design and implement enterprise-scale GenAI applications.
• Build production-grade RAG architectures with vector search and semantic retrieval.
• Develop AI-powered applications using prompt engineering, contextual retrieval, tool calling, and memory management.
• Optimize LLM performance, latency, throughput, hallucination reduction, and response accuracy.
• Design hybrid AI architectures combining structured data, unstructured documents, APIs, and enterprise knowledge sources.
• Implement guardrails, responsible AI controls, content filtering, and compliance frameworks.

Connaissances

Azure

AWS

GCP

Prompt engineering

Memory management

LLM performance optimization

Hybrid AI architectures

Guardrails & compliance

Outils

LangGraph

CrewAI

AutoGen

Semantic Kernel

MCP (Model Context Protocol)

Kafka

Spark

Databricks

Airflow

Hadoop Ecosystem

Delta Lake

Description du poste

RAG Technologies is seeking experts to design and implement enterprise-scale GenAI applications using OpenAI, Claude, Gemini, Llama, and other models. You will build production-grade RAG architectures with vector search and semantic retrieval, and develop AI-powered apps with prompt engineering and memory management.

You will also optimize LLM performance, design hybrid AI architectures, and implement guardrails and compliance frameworks across banking and enterprise data environments.