> Markdown version of [/jobs/ext/2721827-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2721827-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Diverse Lynx LLC - **Location:** Claymont, DE, United States - **Experience:** Expert - **Salary:** $95,400.0 - $106,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Code Review, Computer Programming, Content Analysis, Continuous Integration, Data Structures, Monitoring of Systems, Python (Programming Language), Natural Language Processing, NoSQL, Tensorflow, Standard Sql, Azure Machine Learning, SQL Databases, Systems Integration, Data Logging, Enterprise Software Applications, Cloud Platform System, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Apache Spark, Deep Learning, Generative AI, AI Platforms, Scikit Learn, Information Technology, HuggingFace, Apache Kafka, Machine Learning Operations, Front End Software Development, Restful APIs, Google Shopping, Databricks, Microservices - **Published:** September 4, 2026 - **Apply:** https://www.careerjet.com/job/use88ba61349e2c7e542f50d36589e54e1/eaa ## About the Role Skill: Python, Gen AI, Azure AI, Databricks, Retail Experience Required: 12+ AI Engineer with strong expertise in Python, LLMs, Generative AI, NLP, Databricks, Azure/AWS/GCP, PyTorch/TensorFlow, REST APIs, and SQL/NoSQL. The role involves designing, developing, and deploying scalable AI/GenAI solutions for retail and eCommerce use cases such as search, recommendations, personalization, and AI assistants. Responsible for building and operationalizing ML/LLM models, implementing RAG-based solutions, integrating AI services into enterprise applications, and driving end-to-end delivery through CI/CD and cloud platforms. Experience with MLOps, model monitoring, and cross-functional collaboration is preferred., * Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related technical field. * 3-5 years of experience building and deploying AI/ML-powered applications in production, ideally in consumer, ecommerce, or retail environments. * Strong programming skills in Python and experience with modern ML/AI frameworks (PyTorch, TensorFlow, scikit-learn, Hugging Face, or similar). * Experience with LLMs and NLP (prompt design, embeddings, vector databases, RAG) or strong willingness and demonstrable ability to ramp quickly. * Hands-on experience with cloud platforms (AWS, GCP, or Azure), ML services (SageMaker, Vertex AI, Azure ML) and Databricks. * Experience building and consuming RESTful APIs, working with SQL/NoSQL databases, and deploying services in cloud environments. * Solid understanding of software engineering fundamentals: data structures, algorithms, testing, code reviews, and CI/CD. * Strong communication skills and ability to collaborate with cross-functional partners across time zones. Nice to have * Experience in retail, ecommerce, logistics, or similar high-volume B2C contexts. * Exposure to MLOps tools and concepts (feature stores, model registries, monitoring) and modern data stacks (Spark/Kafka/Airflow/dbt). ## Description We are seeking a highly skilled AI Engineer to design, build, and deploy production-grade AI and Generative AI solutions that power core retail capabilities across merchandising, supply chain, pricing, stores, and digital commerce. This role is deeply hands-on and focused on turning AI models into reliable, scalable, and governed products using modern data and AI platforms Key responsibilities AI System Design and Engineering * Design and implement AI applications for retail scenarios such as product search, recommendations, personalization, content understanding, and customer/associate assistants (chat/voice). * Translate high-level product requirements into technical designs, model choices, and service interfaces that can be implemented and iterated quickly. * Implement LLM- and NLP-based solutions (e.g., retrieval-augmented generation, document Q&A, summarization, classification) for internal knowledge assistants and customer-facing experiences. * Work with front-end and back-end engineers to embed AI capabilities into web, app, store, and internal tools, focusing on usability and performance. Data, modeling, and evaluation * Partner with data engineers to access and prepare data from POS, ecommerce, CRM/loyalty, product catalogs, and supply-chain systems; design data contracts and schemas that support AI applications. * Build and iterate on models using appropriate techniques (traditional ML, deep learning, embeddings, LLMs), balancing accuracy, robustness, and cost. * Set up evaluation pipelines, offline metrics, and online experiments (A/B tests) to measure impact on key KPIs like conversion, engagement, attach rate, in-stock rate, and associate productivity. * Instrument applications with logging, tracing, and dashboards to monitor quality, latency, and errors in production. Engineering excellence * Develop reliable, well-tested APIs, microservices, and jobs that run in cloud environments (AWS/Azure/GCP), using modern DevOps/CI/CD practices. * Own the full lifecycle of features you build from design and implementation through deployment, monitoring, and iteration. * Contribute to shared libraries, templates, and best practices that make it easier for other teams to build AI features consistently. * Collaborate across time zones, maintaining clear communication and documentation for stakeholders. ## Related Videos - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)