Forward Deployed AI Engineer

This is a fully remote position, open to applicants in Hungary.

📋 Description

• Collaborate closely with clients to design and develop AI solutions that address genuine business challenges.

• Transform AI capabilities into practical applications utilized by customers and stakeholders.

• Transition AI solutions from experimental stages and prototypes to fully operational, production-ready systems.

• Validate AI systems through thorough evaluation and enhance their performance measurably.

• Design and implement Retrieval-Augmented Generation (RAG) architectures, agentic workflows, and optimized GenAI applications.

• Structure and orchestrate AI-driven applications utilizing GenAI frameworks.

• Set evaluation baselines and metrics for prompts, retrieval, models, and parameters.

• Oversee experiment tracking, model versioning, observability, and deployment workflows.

• Create automated monitoring, evaluation, and CI/CD pipelines for Machine Learning (ML) and Large Language Model (LLM) systems.

• Design scalable training and inference pipelines.

• Advise clients by translating business problems into technical roadmaps and lead projects from initial scoping to final delivery.

• Articulate architectural decisions to CTOs and collaborate with engineers to troubleshoot pipelines through pair programming.

• Engage hands-on with technologies such as Databricks, PySpark, SQL, Delta Lake, Unity Catalog, MLflow, and Mosaic AI features.

⛳️ Requirements

• Proven experience in building AI systems throughout the complete lifecycle, from experimentation through deployment and monitoring.

• Demonstrated experience in developing production-grade GenAI applications, including RAG architectures, agentic workflows, and fine-tuning processes.

• Familiarity with platforms like OpenAI, Anthropic, Azure AI, or comparable technologies.

• Proficient in GenAI frameworks such as LangChain, LangGraph, Pydantic AI, Hugging Face, or DSPy.

• Evaluation-focused methodology: establish baselines, define relevant metrics, and assess improvements.

• Understanding of LLMOps and MLOps, including experiment tracking, model versioning, observability, and deployment practices.

• Experience in building automated monitoring, evaluation, and CI/CD pipelines for both traditional ML and LLMs.

• Skilled in designing scalable training and inference data pipelines for production environments.

• Extensive Python programming experience with data/ML libraries and the ability to produce clean, testable, and well-structured code.

• Experience deploying or engaging with AI solutions on platforms such as AWS, Azure, or GCP.

• Consultant mindset with client-facing experience: ability to convert business challenges into technical roadmaps and lead projects from inception to completion.

• Databricks experience or certification is advantageous.

• Familiarity with PyTorch or TensorFlow is a plus.

• Knowledge of production LLMOps tooling, including evaluation, monitoring, and drift detection, is a plus.

🏝️ Benefits

• Employment managed through a third-party Employer of Record/payroll provider in accordance with Hungarian employment regulations.

• Access to Databricks learning materials, certifications, and partner academies.

• Regular internal knowledge-sharing sessions and workshops.

• Opportunities to engage hands-on with cutting-edge data and AI technologies, including Databricks and the broader data engineering ecosystem.

• Flexible and collaborative work environment, with options for remote and hybrid working arrangements.

• International collaboration with skilled data and AI professionals across Europe.

• Growth opportunities to enhance technical expertise, consulting abilities, and technical leadership skills.

• Regular team-building activities and chances to connect with colleagues throughout the larger RevoData team.

• Sustainable working practices and a well-being-focused workplace environment.

• A seven-month intensive training program covering certifications, hands-on client project work, and internal knowledge-sharing sessions for candidates without Databricks experience, transitioning to a permanent contract upon meeting agreed milestones.