AI Engineer - Artificial Intelligence Engineer

GAC Solutions; India; In loco; INR 1.200.000 - 1.800.000; Tempo pieno

Descrizione del lavoro

GAC Solutions in India is seeking experienced engineers to build and deploy production-grade LLM-based solutions. You will implement agents, prompts, and integrations with enterprise systems like SharePoint and ERP, while ensuring security, privacy, and responsible AI practices.

Proficiency with Python, REST APIs, and cloud services is essential. Join a team focused on scalable deployment, CI/CD pipelines, and collaboration across Microsoft Copilot Studio, Power Apps, Power Automate, and cloud

Competenze

• Hands-on experience building production-ready LLM solutions.
• Experience with cloud AI services and model deployment (AWS/Azure).
• Strong Python skills and REST API integration knowledge.
• Familiarity with prompt engineering and retrieval augmented generation (RAG).

Mansioni

• Design and deploy LLM-based agents and workflows in production.
• Integrate with enterprise systems (SharePoint, ServiceNow, ERP).
• Ensure security, privacy, and guardrails in AI deployments; perform output evaluation.

Conoscenze

Python

APIs & REST

Prompt engineering

Responsible AI

Security & privacy

CI/CD

Strumenti

Microsoft Copilot Studio

Power Apps

Power Automate

Cursor

AWS Bedrock

SageMaker

Lambda

API Gateway

S3

IAM

OpenSearch

Azure AI Search

SharePoint

Dataverse

Descrizione del lavoro

Hands-on experience building LLM-based solutions in production (not only POCs)

• Microsoft Copilot Studio: building, testing, and publishing agents (topics, actions, knowledge sources, connectors)
• Power Apps: Canvas and Model-driven apps, Dataverse
• Power Automate: cloud flows, approvals, connectors, and integration with agents
• Cursor (or similar AI-assisted coding tools) to speed up development and improve code quality
• AWS: Amazon Bedrock (including Knowledge Bases and Agents), SageMaker, Lambda, API Gateway, S3, and IAM
• Prompt engineering and RAG (Retrieval-Augmented Generation)
• Strong Python; APIs and REST integrations
• Vector databases and search (Amazon OpenSearch, Azure AI Search, or equivalent)
• Integration with enterprise systems (ServiceNow, SharePoint, Dataverse, ERP)
• Responsible AI practices: security, data privacy, guardrails, and output evaluation
• CI/CD, Git, and cloud deployment on AWS and Azure