AI Engineer
Overview
As an AI Engineer working with one of Proactiviti's enterprise clients, you will help enhance productivity through AI-driven experiences and services across core business applications. The team builds foundational platforms and experiences that integrate large language models (LLMs) and real-time intelligence into end-user tools, enabling capabilities such as content generation, navigation, comprehension, and workflow automation.
This role focuses on designing and delivering scalable AI platforms that combine state-of-the-art LLMs with enterprise data and deep application integration. You will collaborate closely with software engineers, researchers, and product managers to translate product needs into well-defined machine learning problems, advance applied LLM capabilities, and bring solutions from prototype to large-scale production.
You will build the engineering systems that make AI reliable in production—developing APIs, platforms, and services around AI features; designing data pipelines and feedback loops; deploying and fine-tuning modern deep learning models; orchestrating prompts and tools; and monitoring AI-specific signals such as drift, hallucinations, safety, and cost alongside traditional reliability metrics.
This is an opportunity to apply cutting-edge AI to real-world, high-impact products used at scale.
ResponsibilitiesFeature delivery and collaborationPartner with product management and engineering teams to co-own scenario goals and translate product requirements into scientific plans and production-ready solutions that meet quality, latency, and cost targets.
Generative AI and advanced technologiesApply expertise in generative AI, large language models, and modern frameworks to build intelligent features, automation, and AI-powered services.
Cloud platform integrationDeploy, integrate, and operate AI-powered solutions within a cloud ecosystem, ensuring security, scalability, reliability, and compliance with best practices.
Continuous learning and knowledge sharingStay current with advances in generative AI and software engineering, propose improvements to development processes, and actively share knowledge with teammates.
Qualifications
Required Qualifications
Bachelors degree in Computer Science or a related technical discipline, or equivalent practical experience
Proven coding experience in one or more of the following languages: C, C++, C#, Java, JavaScript, Python, or similar
AI and machine learning expertise
Hands-on experience with generative AI or machine learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a strong understanding of LLM concepts, embeddings, and prompt engineering
Distributed systems and cloud experience
Familiarity with cloud services, microservices architectures, and distributed storage systems (experience with globally distributed databases is a plus). Ability to design fault-tolerant, secure, and compliant systems at scale
Security requirements
Ability to meet client, customer, and/or government security screening requirements as applicable to the role
Preferred Qualifications
2+ years of experience designing and operating infrastructure systems that run at global scale
Experience deploying AI models into production and building systems that monitor, evaluate, and retrain models automatically
Strong interest in mentoring others and contributing to an inclusive, collaborative team culture
Apply Now
As an AI Engineer working with one of Proactiviti's enterprise clients, you will help enhance productivity through AI-driven experiences and services across core business applications. The team builds foundational platforms and experiences that integrate large language models (LLMs) and real-time intelligence into end-user tools, enabling capabilities such as content generation, navigation, comprehension, and workflow automation.
This role focuses on designing and delivering scalable AI platforms that combine state-of-the-art LLMs with enterprise data and deep application integration. You will collaborate closely with software engineers, researchers, and product managers to translate product needs into well-defined machine learning problems, advance applied LLM capabilities, and bring solutions from prototype to large-scale production.
You will build the engineering systems that make AI reliable in production—developing APIs, platforms, and services around AI features; designing data pipelines and feedback loops; deploying and fine-tuning modern deep learning models; orchestrating prompts and tools; and monitoring AI-specific signals such as drift, hallucinations, safety, and cost alongside traditional reliability metrics.
This is an opportunity to apply cutting-edge AI to real-world, high-impact products used at scale.
ResponsibilitiesFeature delivery and collaborationPartner with product management and engineering teams to co-own scenario goals and translate product requirements into scientific plans and production-ready solutions that meet quality, latency, and cost targets.
Generative AI and advanced technologiesApply expertise in generative AI, large language models, and modern frameworks to build intelligent features, automation, and AI-powered services.
Cloud platform integrationDeploy, integrate, and operate AI-powered solutions within a cloud ecosystem, ensuring security, scalability, reliability, and compliance with best practices.
Continuous learning and knowledge sharingStay current with advances in generative AI and software engineering, propose improvements to development processes, and actively share knowledge with teammates.
Qualifications
Required Qualifications
Bachelors degree in Computer Science or a related technical discipline, or equivalent practical experience
Proven coding experience in one or more of the following languages: C, C++, C#, Java, JavaScript, Python, or similar
AI and machine learning expertise
Hands-on experience with generative AI or machine learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a strong understanding of LLM concepts, embeddings, and prompt engineering
Distributed systems and cloud experience
Familiarity with cloud services, microservices architectures, and distributed storage systems (experience with globally distributed databases is a plus). Ability to design fault-tolerant, secure, and compliant systems at scale
Security requirements
Ability to meet client, customer, and/or government security screening requirements as applicable to the role
Preferred Qualifications
2+ years of experience designing and operating infrastructure systems that run at global scale
Experience deploying AI models into production and building systems that monitor, evaluate, and retrain models automatically
Strong interest in mentoring others and contributing to an inclusive, collaborative team culture
Apply Now