Gen AI Engineer

Smart IT Frame LLC; Halifax; On-site; CAD 100,000 - 150,000; Full time

Job summary

Smart IT Frame LLC in Halifax, Canada seeks an experienced data/ML engineer to build scalable batch and streaming pipelines, optimize data models, and deploy AI services in production.

You will implement DataOps and MLOps automation, design distributed systems with Spark, Kafka, Docker, and Kubernetes, and collaborate across research, engineering and product teams to deliver enterprise-grade AI solutions.

Qualifications

• Master's degree in Computer Science, Software Engineering, or related field with 5+ years in data/software/ML/AI engineering (preferred).
• Advanced Python proficiency with strong software engineering fundamentals (version control, testing).
• Proficiency in SQL and distributed computing (Spark, distributed systems).
• Solid experience with DataOps/MLOps automation, CI/CD and DevOps practices.

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 (CI/CD, data validation, model deployment, monitoring).
• Design, build, and optimize agentic AI systems and LLM-powered applications (RAG pipelines, agent orchestration).
• Develop and integrate AI services into secure, production-grade environments.
• Translate business requirements into technical solutions through cross-functional collaboration.
• Ensure code quality, system reliability, scalability, and observability.

Skills

Python

SQL

Distributed computing

CI/CD

ML workflows

RAG pipelines

LangChain

LangGraph

Education

Master's degree in Computer Science or related field

Tools

GitHub Actions

Docker

Kubernetes

Kafka

Spark

Job description

• 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 (CI/CD, data validation, model deployment, monitoring, drift detection)
• Design, build, and optimize agentic AI systems and LLM-powered applications (RAG pipelines, 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
• Advanced Python proficiency with strong software engineering fundamentals (version control, testing, code reviews)
• Proficiency in SQL and distributed computing (Spark, distributed systems)
• Deep experience with data modeling and feature engineering across the ML lifecycle
• Hands-on experience building LLM applications, RAG pipelines, and agentic AI frameworks (LangChain/LangGraph preferred)
• Expertise designing distributed systems at enterprise scale
• Strong CI/CD and DevOps knowledge (GitHub/GitHub Actions, Docker, Kubernetes)
• Experience with event streaming platforms (Kafka)
• Demonstrated ability to design and deploy hybrid cloud and on-premise systems (AWS, Azure)
• Excellent collaboration and communication skills across engineering, research, and product teams
• Self-directed problem-solving mindset and ability to navigate enterprise complexity
• Master's degree in Computer Science, Software Engineering, or related field with 5+ years in data/software/ML/AI engineering (preferred)