Generative AI Developer
Halifax, Nova Scotia, Canada | T4 Contract | Hybrid (3–4 days/week onsite)
End Client: Leading Canadian Enterprise
About the Role
Our consulting client is looking for an experienced Gen AI Developer to design and build production-grade AI/ML solutions, with a strong focus on Agentic AI, LLM applications, RAG pipelines, MLOps, and distributed data systems.
This role combines Generative AI engineering, data engineering, MLOps, and platform architecture. The successful candidate will work across AI/ML workloads, scalable batch and streaming pipelines, hybrid cloud/on-premise infrastructure, and enterprise-grade deployment and monitoring.
Responsibilities
- Build and maintain scalable batch and streaming data pipelines for ingestion, transformation, and curation.
- Design and optimize data models, feature stores, and storage patterns for AI/ML workloads.
- Implement DataOps and MLOps automation, including CI/CD, data validation, model deployment, monitoring, and drift detection.
- Design, build, and optimize agentic AI systems and LLM-powered applications, including RAG pipelines and agent orchestration.
- Develop and integrate AI services into secure, production-grade environments.
- Design and implement AI systems architecture best practices and standards across the organization.
- Build scalable, resilient cloud and on-premise systems for hosting AI/LLM applications.
- Provide infrastructure design, optimization, and monitoring support.
- Translate business requirements into technical solutions through cross-functional collaboration.
- Ensure code quality, system reliability, scalability, and observability.
What You Bring
- Advanced Python proficiency with strong software engineering fundamentals, including version control, testing, and code reviews.
- Proficiency in SQL and distributed computing, including Apache Spark and distributed systems.
- Big Data experience with Apache Spark, Hadoop, and Scala/Java.
- Deep experience with data modeling and feature engineering across the ML lifecycle.
- Hands-on experience building LLM applications, RAG pipelines, and Agentic AI frameworks.
- Experience with LangChain and/or LangGraph preferred.
- Strong MLOps experience, including CI/CD, data validation, model deployment, monitoring, and drift detection.
- Expertise designing distributed systems at enterprise scale.
- Strong CI/CD and DevOps knowledge using GitHub/GitHub Actions, Docker, and Kubernetes.
- Experience with event streaming platforms such as Kafka.
- Demonstrated ability to design and deploy hybrid cloud and on-premise systems using AWS and Azure.
- Excellent collaboration and communication skills across engineering, research, and product teams.
- Self-directed problem-solving skills and the ability to navigate enterprise complexity.
- Master's degree in Computer Science, Software Engineering, or a related field with 5+ years in data/software/ML/AI engineering preferred.
- React and JavaScript UI development experience is a plus.
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