Data Scientist or ML Engineer

RIVAGO INFOTECH INC.

Warren, NJ, United States

9 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Architectural Patterns Microsoft Azure Cloud Computing Cloud Engineering Computer Programming Continuous Integration Cursor (Graphical User Interface Elements) Python (Programming Language) Node.Js

+18 more

Management of Software Versions Data Logging Google Cloud Spring Cloud Multi-Agent Systems Prompt Engineering Spring-boot Software Security Generative AI Containerization AI Platforms Kubernetes Machine Learning Operations Virtual Agents Restful APIs Network Server Docker Microservices

Requirements

15+ years in software/solution architecture, proven experience as a Data Scientist or ML Engineer with exposure to agent-based AI systems.
Design & Implement Agentic AI systems using agent frameworks (AutoGen, LangGraph, CrewAI, etc.) to build multi-agent and goal-oriented systems.
Proficiency in Prompt Engineering, few-shot prompting, chain-of-thought reasoning, and prompt templates.
Familiarity with cloud-native AI platforms from AWS, Azure, or Google Cloud Platform (e.g., Bedrock, Azure OpenAI, Vertex AI).
Experience on AI for Engineering & working with AI Code Assist tools (e.g., Copilot, Windsurf, Cursor)
Experience working with Vector databases & design & deploy RAG pipelines, MCP Servers & A2A Implement robust LLMOPs - for continuous integration, deployment, monitoring, logging, and troubleshooting mechanisms for GenAI applications.
Develop and promote reusable architectural patterns, best practices, and governance frameworks for GenAI development.
Lead the end-to-end architectural design of Generative AI applications, ensuring scalability, performance, security, cost-effectiveness, and maintainability.
Proficiency in containerization technologies (Docker, Kubernetes) and CI/CD pipelines.
Must have experience working with Microservice architecture using Spring Boot Rest APIs & know API Security, Versioning
Must have experience designing CloudNative applications on any cloud such as AWS, Azure, Google Cloud Platform, Spring Cloud, PCF
Programming proficiency in Python (preferred), and optionally Java/Node.js for integration.
Collaborate with Data Scientists, Product Owners, and Business SMEs to translate business problems into AI-powered solutions.
Exceptional communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences