Fullstack Data Scientist (GenAI)

TL;DR

Fullstack Data Scientist (GenAI): Designing and implementing advanced AI systems based on LLMs, chatbots, and RAG mechanisms with an accent on end-to-end application development and architectural decision-making. Focus on building RAG pipelines, optimizing prompting strategies, and developing agentic AI workflows to solve complex business problems.

Location: Remote or Office (multiple global sites)

Company

hirify.global is a global professional services firm established in 2008, specializing in data and AI with over 1800 talents across 7 global sites.

What you will do

• Lead discovery and solution design for GenAI use cases, translating business problems into technical architectures including LLM selection and RAGs.
• Build end-to-end GenAI applications involving data ingestion, retrieval layers, and orchestration using LangChain, LlamaIndex, or LangGraph.
• Design and implement RAG pipelines with vector databases, hybrid search, rerankers, and evaluation frameworks.
• Perform model selection, prompting strategies, and fine-tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models.
• Implement safety, compliance, and governance controls, including PII handling and human-in-the-loop reviews.
• Mentor data scientists and engineers in GenAI patterns and contribute to internal reusable libraries and templates.

Requirements

• 6+ years of experience in Data Science/AI engineering.
• 4+ years of production-ready Python AI development and 2+ years specifically in production LLM/RAG development.
• Deep understanding of LLM evaluators, validators, guardrails, and orchestration stacks (LangChain, LlamaIndex, etc.).
• Hands-on experience designing or operating MCP servers/clients for LLM agents.
• Familiarity with cloud environments, preferably Azure, GCP, or AWS.
• English: C1+ (Excellent communication skills required)

Nice to have

• Experience with Spark, Databricks, Docker, or Kubernetes for productizing ML solutions.
• Knowledge of CI/CD and DevOps tools such as GitHub Actions, GitLab, or Azure DevOps.
• Experience with agentic AI development frameworks (e.g., BMAD, multi-agent orchestration).

Culture & Benefits

• "Office as an option" model with the ability to choose between remote work or office presence.
• Workation policy allowing work from inspiring locations.
• Unlimited access to the Udemy learning platform and support for technology certificate training.
• Flexibility regarding working hours and preferred form of contract.
• Comprehensive onboarding with a dedicated "Buddy" from day one.