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
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