Gen AI Developer

Job summary

Build and maintain scalable data pipelines and data models, and automate DataOps and MLOps processes across the machine learning lifecycle. Design, deploy, and support production-grade agentic AI and LLM applications, including RAG pipelines, in secure hybrid cloud and on-premise environments.

Job details

Role : Gen AI Developer Location : Halifax, NS (Hybrid) Top 3 skills required for this role: Agentic AI, LLM, RAG Pipelines MLOps Automation (CI/CD, data validation, model deployment, monitoring, drift detection) GitHub/GitHub Actions, Docker, Kubernetes Job Description/ Responsibilities: Big Data: Apache Spark, Hadoop Scala/Java 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, 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 Expectations / Skillset Required: 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) UI development expertise with React and JavaScript (a plus) We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. https://www.e-verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf

What you’ll do

Build and maintain scalable data pipelines and data models, and automate DataOps and MLOps processes across the machine learning lifecycle. Design, deploy, and support production-grade agentic AI and LLM applications, including RAG pipelines, in secure hybrid cloud and on-premise environments.

Requirements

Requires advanced Python, SQL, distributed computing, data modeling, and hands-on experience with LLM applications, RAG pipelines, and agentic AI frameworks. Also requires enterprise-scale distributed systems, CI/CD and DevOps expertise, Kafka experience, and the ability to collaborate across teams; a master's degree and 5+ years of relevant experience are preferred.

Listed skills

• Kubernetes · Preferred
• SQL · Preferred
• Docker · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Agentic AI
• Large Language Models
• Retrieval-Augmented Generation
• MLOps
• Python
• SQL
• Apache Spark
• Distributed Systems
• Data Modeling
• Feature Engineering
• LangChain
• LangGraph
• GitHub Actions
• Docker
• Kubernetes
• Kafka

Job areas

• Technology
• Software
• Data & Analytics
• Engineering

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