Generative AI Engineer

Generative AI Developer

Plano, TX

We are seeking a seasoned Generative AI Developer with expertise in AWS Bedrock and enterprise-grade application development. This role combines advanced AI/ML engineering with the ability to design, build, and deliver scalable, intelligent systems. The ideal candidate will have a proven track record in deploying generative AI solutions, architecting microservices, and integrating AI/LLM capabilities into modern enterprise applications.

Key Responsibilities

• AI System Design & Implementation: Architect and develop scalable AI agent frameworks tailored to business needs, leveraging foundational models and AWS Bedrock.
• Bedrock Model Expertise: Fine-tune and deploy Bedrock models (LLMs, multimodal models) for use cases such as vector-based retrieval and Retrieval-Augmented Generation (RAG).
• Enterprise Application Development: Design, develop, and deliver multi-tier, enterprise-grade applications with a strong focus on microservices, REST APIs, and Kafka-based integrations.
• Optimization & Reliability: Enhance model performance while balancing computational cost, ensuring deployed AI systems are robust, accurate, and maintainable.
• Innovation & Integration: Actively integrate AI/ML capabilities and LLM-based tooling into modern software systems, staying current on emerging technologies.
• Collaboration: Work closely with data scientists, engineers, product managers, and stakeholders to translate AI research into production-ready systems.
• Leadership & Best Practices: Mentor teams, drive engineering excellence through TDD, BDD, and DoD, and ensure delivery of high-quality software solutions.
• Data & Infrastructure: Manage large datasets, model lifecycle tools (MLflow, Kubeflow), and containerization (Docker, Kubernetes) for reproducible, scalable environments.

Required Skills & Experience

Technical Skills

• AI/ML & LLM: AWS Bedrock, OpenAI GPT-4 API, LangChain, Hugging Face Transformers, RAG pipelines, LLM orchestration, prompt engineering, AI-assisted coding tools (GitHub Copilot)
• Languages: Python (scripting & AI automation), Java (working knowledge)
• Frameworks: Spring Boot, Spring AI, Microservices, Apache Camel, Fuse ESB
• Messaging: Apache Kafka, ActiveMQ Artemis, event-driven architecture
• Frontend: React, HTML5, CSS3, AJAX, jQuery
• Cloud & DevOps: AWS (EC2, S3, Lambda, SageMaker), Docker, Kubernetes, Jenkins, Ansible, Git
• Databases: Oracle (9i/10g/12c), vector databases (Pinecone, others)
• Testing & Tools: Cucumber (BDD), SonarQube, Postman, JIRA, Maven, Gradle, Apache Spark
• Operating Systems: Windows, UNIX, IBM AIX

Experience: Several years of experience in AI/ML engineering, with cloud-native, generative AI integrations and familiarity with enterprise application development practices.