Artificial Intelligence Engineer

AI Integration Engineer

Location - Remote only on W2

Job Summary

We are seeking a highly skilled AI Integration Engineer to design, develop, and maintain integrations between AI/ML systems and third-party platforms. The ideal candidate will have strong experience in API integrations, cloud platforms, and AI services, with a focus on enabling seamless data flow and automation across enterprise systems.

Key Responsibilities

• Design and implement integration solutions between internal systems and third-party platforms (SaaS, APIs, enterprise tools).
• Integrate AI/ML models and services (Azure AI, OpenAI, AWS AI, GCP AI) into enterprise applications.
• Develop and maintain REST APIs, webhooks, and middleware for seamless communication between systems.
• Work with data engineering teams to enable efficient data ingestion and processing pipelines.
• Implement scalable, secure, and high-performance integration architectures.
• Automate workflows using AI-driven solutions and orchestration tools.
• Troubleshoot and resolve integration issues, performance bottlenecks, and failures.
• Ensure data security, compliance, and governance standards are met.
• Collaborate with cross-functional teams including product, engineering, and business stakeholders.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field
• 5--10 years of experience in software development or integration engineering
• Strong experience in API development and integration (REST, GraphQL, Webhooks)
• Hands-on experience with AI platforms:
  • Azure AI Services / OpenAI
  • AWS AI/ML services
  • Google AI / Vertex AI
• Strong programming skills in Python, Java, or Node.js
• Experience with cloud platforms (Azure, AWS, or GCP)
• Knowledge of data formats and protocols (JSON, XML, OAuth, JWT)
• Familiarity with event-driven architectures and messaging systems (Kafka, Service Bus, RabbitMQ)

Preferred Qualifications

• Experience integrating with SaaS tools (Salesforce, ServiceNow, SAP, Workday, etc.)
• Knowledge of ETL pipelines and data engineering concepts
• Hands-on experience with workflow/orchestration tools (Airflow, Logic Apps, Zapier, MuleSoft)
• Experience with PowerShell or scripting for automation
• Exposure to microservices architecture and containerization (Docker, Kubernetes)
• Understanding of DevOps practices and CI/CD pipelines

Key Competencies

• Strong problem-solving and analytical skills
• Excellent debugging and troubleshooting abilities
• Strong communication and stakeholder management
• Ability to work in agile and fast-paced environments

Nice to Have

• AI model deployment experience (ML Ops)
• Experience with LLM integrations (OpenAI, ChatGPT, Azure OpenAI)
• Knowledge of data governance and security best practices