AI Engineer

Job description

Company Description

BLeader is an end-to-end data firm renowned for its ability to understand executive mindsets and craft leading strategies. Our team partners with organizations throughout their data transformation journey to achieve measurable business results. Leveraging years of experience and best-in-class expertise, BLeader transcends technical tasks to generate real, tangible value for clients across various industries.

About the Role

We're seeking an experienced AI Engineer to join our team and drive the implementation of scalable, production-ready AI solutions. This role is perfect for a Data Engineer or software engineering professional who thrives on building robust AI systems, managing cloud infrastructure, and creating efficient data pipelines and automation workflows.

Unlike traditional data science roles, this position focuses on the data engineering and infrastructure backbone that makes AI systems work reliably at scale in production environments.

What You'll Do

System Architecture & Integration

• Design and implement end-to-end AI solution architectures
• Build robust APIs and wrappers for AI models and services
• Integrate AI capabilities into existing enterprise systems
• Evaluate and recommend AI tools, frameworks, and platforms

Cloud Infrastructure Management

• Deploy and manage AI workloads across cloud platforms (AWS, Azure, GCP)
• Optimize infrastructure costs and performance for AI applications
• Implement containerization and orchestration (Docker, Kubernetes)
• Set up monitoring, logging, and alerting for AI systems

AI Model Operations & Automation

• Build MLOps pipelines for model deployment and monitoring
• Create automated workflows for model training, testing, and deployment
• Develop custom model serving solutions and API endpoints
• Implement A/B testing frameworks for model performance evaluation

Data Infrastructure & Pipelines

• Design and build scalable data pipelines for AI/ML workloads
• Implement real-time and batch data processing systems
• Create data transformation and feature engineering pipelines
• Build data quality monitoring and validation frameworks
• Optimize data flow and storage for AI model training and inference

What We're Looking For

Core Engineering & Data Skills:

• 5+ years of data engineering, software engineering, or DevOps experience
• Strong proficiency in Python and SQL, plus experience with Scala, Java, or Go
• Extensive experience with data pipeline development and ETL/ELT processes
• Experience with cloud platforms (AWS/Azure/GCP) and infrastructure as code
• Solid understanding of big data technologies (Spark, Kafka, Airflow)
• Experience with data warehousing, data lakes, and modern data stack
• Database management experience (SQL and NoSQL, data modeling)

AI Engineering Experience:

• Hands-on experience with AI/ML model deployment and serving
• Knowledge of AI frameworks (TensorFlow, PyTorch, Hugging Face, OpenAI APIs)
• Experience building APIs and microservices for AI applications
• Understanding of model optimization, quantization, and inference acceleration
• Familiarity with vector databases and embedding systems

Automation & DevOps:

• Experience with automation tools (Terraform, Ansible, Jenkins)
• Knowledge of monitoring and observability tools (Prometheus, Grafana, ELK)
• Understanding of security best practices for AI systems
• Experience with data pipeline orchestration (Airflow, Prefect)

Ready to Build the Future of AI?

Join us in creating AI solutions that actually work in the real world. If you're passionate about turning AI concepts into reliable, scalable systems that users can depend on, we'd love to hear from you.

Apply now with your resume and a brief note about your most challenging AI engineering project.

We are an equal opportunity employer committed to diversity and inclusion.