AI & Developer Digital Marketing Strategist

Job highlights Identified by Google from the original job post Qualifications • Languages: Python, SQL, JavaScript (Node.js/TypeScript) for APIs • Data Engineering: Snowflake, Databricks, dbt, Kafka, Spark • Python programming skills for data pipelines, ML experimentation, and API integrations • Experience working in cloud environments such as AWS, GCP, or Azure • Familiarity with containerisation, microservices, and infrastructure as code • Knowledge of ML lifecycle management and deployment best practices • Interest in LLMs and generative AI tooling, with an appetite to learn and experiment • Good communication skills and the ability to collaborate across engineering, product, and data science teams • Data Engineers with cloud-scale experience looking to add ML or AI integrations to their work • Machine Learning Engineers who want to productionise models and scale pipelines • Software Engineers (Python or JavaScript) with interest in data-centric AI products • Cloud or DevOps Engineers with MLOps experience • AI Engineers with applied experience in LLM integrations or agentic frameworks • Projects span predictive models, LLM-enhanced applications, recommendation systems, and large-scale data integrations • These roles are perfect for engineers who love solving complex problems, enjoy collaborating in cross-functional teams, and want to stay on the leading edge of applied AI and MLOps • 12 more items(s) Benefits • Salary Bracket: $130,000 to $190,000 base plus performance bonuses and comprehensive benefits • Location: Fully remote within the US, HQ in Dallas Texas and New York Responsibilities • Career Outlook: Opportunities to grow vertically up the ranks as an AI Engineer or AI Lead, or team leadership, business/technology strategy or architecture roles as the company expands • Design, build, and maintain scalable data pipelines and ML infrastructure in a cloud-native environment • Integrate AI and LLM-based solutions into production systems, working closely with software engineering and product teams • Implement CI/CD for ML workflows and manage containerised deployments • Support data governance, monitoring, and reliability of machine learning systems • Collaborate on applied AI use cases, from predictive analytics to generative AI integrations • MLOps and Cloud: AWS (SageMaker, S3, Lambda), Azure ML, Terraform, Kubernetes, Docker • ML/AI Frameworks: scikit-learn, TensorFlow, PyTorch, LangChain, OpenAI API integrations • Workflow and Orchestration: Airflow, Prefect, MLflow, Metaflow • Version Control and CI/CD: Git, GitHub Actions, GitLab, Azure DevOps • You will join a growing engineering team delivering real-world AI solutions • You will help the team build robust, maintainable, production-ready AI services that deliver business value quickly • 9 more items(s) More job highlights Job description Aventis Solutions is igniting the AI revolution: The AI Executive Podcast is now live online via:

• YouTube

• Spotify

• Amazon Music

In other news, Aventis Solutions is supporting a fully remote, fast-scaling US FinTech firm in hiring 4x AI Engineers or MLOps Data Engineers to help build production-ready AI systems and modern data platforms. These roles are fully remote across the US, with a coll...aborative team culture, strong engineering leadership, and a mission to bring advanced AI capabilities into real-world products.

Key Details:

• Salary Bracket: $130,000 to $190,000 base plus performance bonuses and comprehensive benefits

• Location: Fully remote within the US, HQ in Dallas Texas and New York

• Career Outlook: Opportunities to grow vertically up the ranks as an AI Engineer or AI Lead, or team leadership, business/technology strategy or architecture roles as the company expands

Key Responsibilities:

• Design, build, and maintain scalable data pipelines and ML infrastructure in a cloud-native environment

• Integrate AI and LLM-based solutions into production systems, working closely with software engineering and product teams

• Implement CI/CD for ML workflows and manage containerised deployments

• Support data governance, monitoring, and reliability of machine learning systems

• Collaborate on applied AI use cases, from predictive analytics to generative AI integrations

Tech Stacks:

• Languages: Python, SQL, JavaScript (Node.js/TypeScript) for APIs

• Data Engineering: Snowflake, Databricks, dbt, Kafka, Spark

• MLOps and Cloud: AWS (SageMaker, S3, Lambda), Azure ML, Terraform, Kubernetes, Docker

• ML/AI Frameworks: scikit-learn, TensorFlow, PyTorch, LangChain, OpenAI API integrations

• Workflow and Orchestration: Airflow, Prefect, MLflow, Metaflow

• Version Control and CI/CD: Git, GitHub Actions, GitLab, Azure DevOps

What the Team is Looking For:

• Python programming skills for data pipelines, ML experimentation, and API integrations

• Experience working in cloud environments such as AWS, GCP, or Azure

• Familiarity with containerisation, microservices, and infrastructure as code

• Knowledge of ML lifecycle management and deployment best practices

• Interest in LLMs and generative AI tooling, with an appetite to learn and experiment

• Good communication skills and the ability to collaborate across engineering, product, and data science teams

Example Backgrounds:

• Data Engineers with cloud-scale experience looking to add ML or AI integrations to their work

• Machine Learning Engineers who want to productionise models and scale pipelines

• Software Engineers (Python or JavaScript) with interest in data-centric AI products

• Cloud or DevOps Engineers with MLOps experience

• AI Engineers with applied experience in LLM integrations or agentic frameworks

Roles Overview:

You will join a growing engineering team delivering real-world AI solutions.

Projects span predictive models, LLM-enhanced applications, recommendation systems, and large-scale data integrations.

You will help the team build robust, maintainable, production-ready AI services that deliver business value quickly.

These roles are perfect for engineers who love solving complex problems, enjoy collaborating in cross-functional teams, and want to stay on the leading edge of applied AI and MLOps.

If you want to work fully remotely in a company that values autonomy, learning, and high-quality engineering, this is your opportunity.

Believe the hype!

Interested?

Please submit your CV via LinkedIn or message Billy Hall for further information.

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