Artificial Intelligence Engineer Job at TalentOla in Columbus
TalentOla, Columbus, OH, United States
Responsibilities
Segmentation logic and data extension mappings
Develop prompting frameworks, agent orchestration logic, and reasoning loops for reliable autonomous workflow creation.
Collaborate with DSL engineers to ensure the AI models can generate valid, safe, and expressive DSL instructions.
Implement fine-tuning, RAG, and model-conditioning pipelines to improve accuracy and reduce hallucinations.
Build evaluation, scoring, and validation systems for AI-generated journeys before deployment.
Integrate AI agents with SFMC APIs (REST & SOAP) to execute and test generated workflows.
Develop guardrails, safety layers, and constraint‑based generation patterns to ensure compliance with marketing and regulatory rules.
Work with marketing operations and CRM teams to encode real‑world campaign logic into model behaviors.
Monitor and optimize model performance, latency, and cost across cloud environments.
Required Skills & Experience
Strong experience with LLMs, generative AI, and agentic architectures (OpenAI, Anthropic, Llama, etc.).
Fine‑tuning or supervised instruction training
Multi‑agent orchestration frameworks
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, HuggingFace).
Experience building production‑grade ML systems with CI/CD, monitoring, and observability.
Understanding of Salesforce Marketing Cloud concepts:
Journey Builder
Email Studio
Data Extensions
Strong grasp of API integration, especially REST/SOAP patterns.
Experience translating business workflows into structured, machine‑interpretable logic.
Preferred Qualifications
Experience with AI‑driven workflow automation or autonomous agents.
Familiarity with AMPscript, SSJS, and SFMC personalization.
Background in marketing automation, CRM systems, or lifecycle marketing.
Knowledge of reinforcement learning, constrained decoding, or rule‑based generation.
Experience with cloud platforms (AWS, Azure, GCP) and containerized deployments (Docker, Kubernetes).
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Segmentation logic and data extension mappings
Develop prompting frameworks, agent orchestration logic, and reasoning loops for reliable autonomous workflow creation.
Collaborate with DSL engineers to ensure the AI models can generate valid, safe, and expressive DSL instructions.
Implement fine-tuning, RAG, and model-conditioning pipelines to improve accuracy and reduce hallucinations.
Build evaluation, scoring, and validation systems for AI-generated journeys before deployment.
Integrate AI agents with SFMC APIs (REST & SOAP) to execute and test generated workflows.
Develop guardrails, safety layers, and constraint‑based generation patterns to ensure compliance with marketing and regulatory rules.
Work with marketing operations and CRM teams to encode real‑world campaign logic into model behaviors.
Monitor and optimize model performance, latency, and cost across cloud environments.
Required Skills & Experience
Strong experience with LLMs, generative AI, and agentic architectures (OpenAI, Anthropic, Llama, etc.).
Fine‑tuning or supervised instruction training
Multi‑agent orchestration frameworks
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, HuggingFace).
Experience building production‑grade ML systems with CI/CD, monitoring, and observability.
Understanding of Salesforce Marketing Cloud concepts:
Journey Builder
Email Studio
Data Extensions
Strong grasp of API integration, especially REST/SOAP patterns.
Experience translating business workflows into structured, machine‑interpretable logic.
Preferred Qualifications
Experience with AI‑driven workflow automation or autonomous agents.
Familiarity with AMPscript, SSJS, and SFMC personalization.
Background in marketing automation, CRM systems, or lifecycle marketing.
Knowledge of reinforcement learning, constrained decoding, or rule‑based generation.
Experience with cloud platforms (AWS, Azure, GCP) and containerized deployments (Docker, Kubernetes).
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