Medior/Senior AI Engineer

Employer · SnapSoft

Software developerApplications developerSystems analystFull-time

Budapest

SnapSoft is a leading AWS Premier Tier Partner specializing in cloud migrations, Generative AI (GenAI), DevOps, and application development. As an AI Engineer, you will design and implement Python-based generative AI services that combine Large Language Models (LLMs), retrieval, and external systems into working automation. You will join our Operations team to build SnapSoft's internal agentic portfolio before moving on to AI/ML client delivery projects after the first year.

Tasks

  • Design and build agentic systems that plan, call tools and automate real business workflows.
  • Design and build multi-agent (agent-to-agent) solutions in which agents hand work to each other, review it and escalate to a human when needed.
  • Develop LLM-powered applications, including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration.
  • Work with vector databases and search: indexing strategies, hybrid and semantic search, relevance tuning.
  • Integrate AI services with external systems through APIs: REST endpoints, authentication, webhooks, third-party and client-side SaaS platforms.
  • Perform prompt engineering, model selection and systematic evaluation of LLM outputs.
  • Build scalable Python services and the data flows behind them, including AI-driven data access such as Text2SQL.
  • Deploy AI solutions on cloud infrastructure (e.g. on AWS: Bedrock, SageMaker, Lambda, Textract).
  • Take solutions from POC and early feedback to production release, then prepare them for handover to operations.
  • Align your architecture with the delivery team's existing platforms and standards, and work closely with them for technical guidance.
  • Experience building AI agents: you have put at least one agentic solution into production that optimised, automated or replaced one or more business processes.
  • Strong proficiency in Python and hands-on experience with the GenAI ecosystem.
  • Solid understanding of LLM application concepts: RAG, embeddings, vector databases, tool calling, agent patterns, prompt engineering and evaluation.
  • Proven experience designing, consuming and integrating APIs, and connecting AI services to existing systems.
  • Hands-on experience deploying solutions on at least one major cloud platform.
  • Good command of SQL and a working understanding of core data engineering concepts.
  • Excellent problem-solving and communication skills.
  • Fluent English.

Posted Nov 2, 2026 · Updated yesterday · 0 views