Integration Engineers

We are seeking a skilled AI / ML Engineer to design, build, and deploy scalable machine learning and AI solutions.

The ideal candidate will have hands‑on experience with LLMs, Retrieval‑Augmented Generation (RAG), MLOps pipelines, and system integrations, while ensuring compliance and security standards are met.

This role involves close collaboration with data scientists, engineers, and business stakeholders to deliver production‑ready AI systems that drive business value.

Key Responsibilities

• Develop and optimize AI / ML models with LLMs, RAG, vector databases, and modern ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Implement MLOps practices, including CI / CD for ML, model deployment, monitoring, and retraining workflows.
• Design and integrate systems using REST, GraphQL, and gRPC APIs, as well as microservices architecture.
• Utilize Docker, Kubernetes, and orchestration tools for containerization and scaling AI workloads.
• Build and maintain ETL / ELT pipelines to process structured and unstructured data across SQL / NoSQL databases.
• Deploy and manage AI workloads on cloud platforms (AWS, Azure, or GCP).
• Ensure compliance with security and regulatory standards (OAuth, JWT, data encryption, GDPR, HIPAA).
• Write clean, efficient code in Python, with additional integrations in Java, Go, or Leverage Terraform, Ansible, and automation scripts for cloud infrastructure and deployment automation.
• Collaborate with cross‑functional teams to ensure seamless integration of AI solutions into business applications.

Requirements

Qualifications

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