AI Engineer – LLMs & Python

Intellibus; New York (NY); On-site; USD 103,000 - 117,000; Full time

Job summary

Intellibus designs AI-enabled platforms for FinTech firms, turning AI capabilities into practical applications. We seek hands-on AI engineers to design, develop, and deploy production-grade AI-powered apps using LLMs, Python, prompts, SQL, and modern data platforms.

You will work across the AI application lifecycle, from requirements and data prep to building LLM integrations, evaluating outputs, and deploying reliable solutions for enterprise environments.

Qualifications

• Experience building production AI applications with Python and LLMs.
• Strong SQL skills and data modeling experience.
• Experience integrating AI capabilities into enterprise apps.
• Familiarity with API integrations and data pipelines.
• Knowledge of Azure data services and Microsoft Fabric.
• Ability to write maintainable, testable production code.

Responsibilities

• Build and integrate applications powered by large language models.
• Develop, test, and refine prompts to improve response quality, consistency, and relevance.
• Design reusable AI workflows and integrate LLM capabilities into existing enterprise applications.
• Evaluate model outputs, manage edge cases, and improve the reliability of AI-generated responses.
• Apply appropriate validation, security, and error-handling practices.
• Develop production-quality Python applications, services, and automation.
• Build APIs and backend components that connect AI models, data sources, and enterprise systems.
• Write maintainable code, perform debugging, and contribute to testing and deployment.
• Work with SQL, relational data, and structured or unstructured data sources.
• Develop data models and data-processing workflows that support AI applications.
• Prepare, validate, transform, and retrieve data for LLM-based solutions.
• Use Microsoft Fabric and Azure data services to support data integration and AI workflows.
• Develop and deploy AI-enabled solutions using Microsoft Azure.
• Integrate AI services with enterprise applications, APIs, and data platforms.
• Monitor application performance, troubleshoot issues, and optimize reliability.
• Collaborate with engineering and business teams to deliver working solutions against defined requirements.

Skills

Python

LLMs

Prompt engineering

SQL

Azure

Microsoft Fabric

API integration

Tools

Azure services

APIs

Job description

Intellibus designs and engineers technology platforms for established FinTech and financial-services firms. We build production-grade systems that help organizations solve complex business problems through software engineering, data, and emerging technologies.

We are looking for engineers who can turn AI capabilities into practical, reliable applications that deliver measurable business value.

The AI Engineer Role

We are hiring hands-on AI Engineers to design, develop, integrate, and deploy AI-powered applications using large language models (LLMs), Python, prompt engineering, SQL, and modern data platforms.

You will work across the AI application lifecycle, from understanding business requirements and preparing data to building LLM integrations, evaluating outputs, and deploying production-ready solutions.

This is an engineering role, not a research-only or strategy-only position. We need candidates who can write code, work directly with data, troubleshoot technical issues, and deliver functioning applications.

Experience with Microsoft Azure and Microsoft Fabric is especially relevant.

What You Will Do

• Build and integrate applications powered by large language models.
• Develop, test, and refine prompts to improve response quality, consistency, and relevance.
• Design reusable AI workflows and integrate LLM capabilities into existing enterprise applications.
• Evaluate model outputs, manage edge cases, and improve the reliability of AI-generated responses.
• Apply appropriate validation, security, and error-handling practices.

Python Development

• Develop production-quality Python applications, services, and automation.
• Build APIs and backend components that connect AI models, data sources, and enterprise systems.
• Write maintainable code, perform debugging, and contribute to testing and deployment.
• Work with SQL, relational data, and structured or unstructured data sources.
• Develop data models and data-processing workflows that support AI applications.
• Prepare, validate, transform, and retrieve data for LLM-based solutions.
• Use Microsoft Fabric and Azure data services to support data integration and AI workflows.
• Develop and deploy AI-enabled solutions using Microsoft Azure.
• Integrate AI services with enterprise applications, APIs, and data platforms.
• Monitor application performance, troubleshoot issues, and optimize reliability.
• Collaborate with engineering and business teams to deliver working solutions against defined requirements.

What Sets You Apart

We are looking for engineers who demonstrate several of the following:

• You have hands-on experience building applications using Python.
• You have practical experience working with LLMs, generative AI, and prompt engineering.
• You understand how to integrate AI capabilities into real applications rather than relying solely on AI tools.
• You have strong SQL skills and an understanding of data modeling.
• You have experience with Microsoft Azure and, ideally, Microsoft Fabric.
• You can work with APIs, data pipelines, and enterprise application integrations.
• You understand testing, debugging, and production deployment.
• You can explain technical decisions and deliver solutions independently.

Data: SQL, data modeling, data transformation, data integration

Data Platform: Microsoft Fabric

Compensation: $75 - $85 / Hour

Our Process

• Initial Screening: 15-minute video call with the Recruiting Team.
• Assessments: One proctored GQ multiple-choice assessment and a SlideWare presentation (under 2 hours).
• Interview Rounds: Three 30-minute video interviews with the Technical Team, Project Lead, and Executive Team.
• Offer: Final decision and job offer.