AI Development Engineer (Codebeamer)

TL;DR

AI Development Engineer (Codebeamer): Driving complex AI initiatives end-to-end and shaping hirify.global’s AI strategy for Codebeamer with an accent on designing and delivering production-grade AI systems and integrating AI capabilities into enterprise products. Focus on collaborating across product, engineering, architecture, and research teams to solve high-impact problems and elevate AI maturity within Codebeamer.

Location: Budapest, Hungary

Company

hirify.global's software brings the physical and digital worlds together, enabling companies to improve operations, create better products, and empower people in all aspects of their business.

What you will do

• Lead the design and development of AI-powered features within the Codebeamer platform.
• Architect scalable machine learning pipelines, including data ingestion, preprocessing, model training, evaluation, deployment, and monitoring.
• Evaluate and integrate AI frameworks, LLMs, and emerging AI technologies into existing software systems.
• Provide technical leadership across multiple teams, influencing best practices and architecture decisions.
• Collaborate closely with product managers to translate user needs into AI-driven capabilities.
• Ensure model performance, security, reliability, and compliance standards.

Requirements

• Extensive hands-on experience in AI/ML development, including NLP, LLMs, predictive modeling, or recommendation systems.
• Proven experience developing and shipping production-grade AI features.
• Strong Python or Java development skills; familiarity with frameworks like TensorFlow, PyTorch, Keras, or HuggingFace.
• Experience with LLM integration, RAG, vector databases, and model fine-tuning.
• Strong understanding of data structures, algorithms, and distributed computing.
• Prior experience leading technical initiatives or cross-functional AI/ML projects.

Nice to have

• Experience with enterprise-grade, scalable software systems.
• Familiarity with Docker, Kubernetes, and MLOps tooling (e.g., MLflow, Kubeflow, SageMaker).
• Expertise in cloud environments (AWS, Azure).
• Understanding of security, compliance, and governance for AI systems.
• Ability to drive architectural decisions and influence AI strategy at scale.

Culture & Benefits

• Opportunities for team members to explore, learn, and grow.
• See ideas come to life and celebrating the differences that make us who we are and the work we do possible.