AI Engineer

TL;DR

AI Engineer (AI): Design, build, and deploy machine learning models and AI agent workflows using Python, PyTorch, and LangChain with an accent on scalable enterprise systems, RAG architectures, and LLM integration. Focus on orchestrating agent behaviors, optimizing inference with AWS Bedrock and SageMaker, and processing big data with Apache Spark.

Location: Hybrid in Bucharest, Romania

Company

25-year-old Vienna-based IT consulting firm delivering end-to-end services including custom software development, AI frameworks, and digital transformation across industries like BSFI, telecom, retail, and energy, with a Bucharest office and global presence.

What you will do

• Design, build, and deploy ML models using Python and PyTorch for robust, scalable performance.
• Orchestrate AI agent workflows with LangChain, LiveKit, and OpenAIAgentsSDK for chatbots, productivity assistants, and document intelligence.
• Validate agent behavior using MCP, Guardrails, and structured instructions for safety and compliance.
• Integrate AWS Bedrock for LLMs, enable RAG with embeddings, and optimize inference in enterprise systems.
• Automate AI workflows with n8n and manage LLM flows using OpenWebUI in hybrid environments.
• Use AWS SageMaker for ML training/deployment and Apache Spark on EMR for big data processing.

Requirements

• Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or related field.
• 4+ years in ML or AI engineering with experience deploying models at scale.
• Strong Python programming and proficiency in NLP and LLMs.
• Hands-on with AWS services (SageMaker, Bedrock, EMR) or equivalents for AI pipelines.
• Clean, production-level code with best practices (version control, testing, CI/CD).
• Strong analytical, problem-solving, communication, and collaboration skills.
• Good English (upper intermediate).

Culture & Benefits

• Premium medical package, lunch tickets, Pluxee Card, Bookster subscription.
• 13th salary, yearly bonuses, flexible working with openness to remote.
• Supportive culture emphasizing ownership, autonomy, work-life balance, flat hierarchy.
• Team events, international exposure, project choice aligned with career goals.
• Learning platforms (Pluralsight, Udemy), certifications, mentorship, career growth.