Senior GenAi Engineer - Remote

YO IT Consulting; Warszawa; On-site; PLN 70,000 - 100,000; Full time

Job summary

YO IT Consulting is seeking a GenAI Engineer to design and operationalize generative AI capabilities. This role involves building models for enterprise use cases, working with LLMs, and optimizing solutions. The ideal candidate will have 5–9 years of experience in AI and strong skills in Python and GenAI frameworks. The position is permanent remote with a focus on impactful, scalable solutions in a fast-paced environment.

Qualifications

• 5–9 years in data science, ML engineering, or AI development, with at least 2 years focused on generative AI.
• Strong hands-on experience with LLMs, transformers, embeddings, and vector databases.
• Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning).
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.

Responsibilities

• Design, train, fine-tune, and evaluate generative AI models for enterprise use cases.
• Develop and optimize prompt engineering and fine-tuning workflows.
• Partner with business teams to identify, evaluate, and prioritize GenAI use cases.
• Create solution blueprints, prototypes, and POCs to demonstrate business value.

Skills

LLMs

Python

GenAI frameworks

Problem-solving

Communication

Education

Master’s or Bachelor’s degree in Computer Science, Data Science, AI, or related field

Tools

AWS

Azure

GCP

Docker

Kubernetes

Job description

Role Overview

The GenAI Engineer will be responsible for building and operationalizing Generative AI capabilities across platforms and client engagements. This role blends hands‑on model development, prompt and pipeline engineering, MLOps, and business‑facing solution design.

The ideal candidate combines deep technical expertise in LLMs and GenAI frameworks with strong business understanding, enabling them to translate real‑world problems into scalable GenAI solutions with measurable impact.

Key Responsibilities

• Design, train, fine‑tune, and evaluate generative AI models (LLMs, multimodal models) for enterprise use cases.
• Develop and optimize prompt engineering, RAG pipelines, agents, and fine‑tuning workflows.
• Work with open‑source and commercial LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.).
• Implement guardrails, safety mechanisms, and hallucination mitigation techniques.
• Partner with business, consulting, and product teams to identify, evaluate, and prioritize GenAI use cases.
• Translate business problems into clear GenAI solution architectures and success metrics.
• Define ROI, feasibility, and scalability of GenAI initiatives.
• Create solution blueprints, prototypes, and POCs to demonstrate business value.
• Design and manage data pipelines for GenAI training, fine‑tuning, and inference.
• Build scalable, secure, and cost‑efficient GenAI systems for production environments.
• Collaborate with engineering teams on deployment, monitoring, and retraining strategies.
• Monitor model performance, latency, cost, and drift in production.
• Ensure responsible, ethical, and compliant use of generative AI.
• Implement explainability, auditability, and traceability mechanisms.
• Address data privacy, IP protection, and regulatory constraints (e.g., GDPR).
• Define and enforce GenAI best practices, standards, and usage guidelines.

Location

Europe – Permanent Remote

Experience

5–9 years in data science, ML engineering, or AI development, with at least 2 years focused on generative AI.

Qualifications

• Master’s or Bachelor’s degree in Computer Science, Data Science, AI, or a related field.
• Strong hands‑on experience with LLMs, transformers, embeddings, and vector databases.
• Proficiency in Python and GenAI frameworks such as LangChain, LlamaIndex, Haystack, Hugging Face, etc.
• Experience with fine‑tuning techniques (LoRA, PEFT, instruction tuning).
• Hands‑on experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
• Candidate must be from a life‑science background – pharmaceutical, consumer care, MedTech, hospitals, clinics, or health insurance.

Preferred Qualifications

Experience working in consulting or enterprise product environments.

Key Skills & Attributes

• Deep understanding of LLMs, RAG, agents, and multimodal AI.
• Business orientation – ability to define GenAI use cases tied to measurable business outcomes.
• Strong problem‑solving skills – translate ambiguity into structured AI solutions.
• Engineering mindset – build scalable, secure, and production‑ready systems.
• Excellent communication – explain GenAI concepts to non‑technical stakeholders.
• Ownership – take end‑to‑end responsibility from idea to production.
• Adaptability – thrive in a fast‑paced, rapidly evolving AI landscape.
• Ethical awareness – focus on responsible AI and governance.