- Company Name
- Wavestone
- Job Title
- Consultant.e AI Engineer
- Job Description
-
**Job Title**
Consultant AI Engineer
**Role Summary**
Design, develop, and industrialize AI solutions for large enterprises, transforming business problems into production‑ready ML/LLM models and autonomous agents. Leverages cross‑functional expertise in data engineering, MLOps, and business strategy to deliver high‑impact, responsible AI deployments.
**Expectations**
- Deliver end‑to‑end AI projects: use case discovery, platform design, model training, deployment, and ongoing monitoring.
- Collaborate with client teams, data scientists, architects, and change‑management specialists across global engagements.
- Maintain high standards of reliability, security, and compliance (GDPR, data sovereignty).
- Continuously evaluate emerging frameworks and multimodal technologies to keep solutions state‑of‑the‑art.
**Key Responsibilities**
- Conduct data preprocessing, fine‑tuning, retrieval‑augmentation (RAG), and embedding creation for ML/LLM solutions.
- Build automation and optimization algorithms to accelerate and secure business processes.
- Develop operational AI agents (copilots, assistants, orchestrations) using Python or low/no‑code platforms.
- Industrialize models and agents via CI/CD pipelines, AIOps/MLOps/LLMOps, observability, monitoring, and security controls.
- Test new agentic frameworks (LangChain, Semantic Kernel, multi‑agent orchestration) and emerging frameworks.
- Participate in knowledge‑sharing sessions, contribute to pre‑sales, and enhance internal AI assets.
**Required Skills**
- Proficiency in Python, foundational knowledge of ML/LLM, and experience with agentic frameworks (LangChain, Semantic Kernel).
- Strong software‑engineering fundamentals; experience with API frameworks (FastAPI, Flask, Streamlit) and version control (Git, GitLab/GitHub).
- Practical knowledge or willingness to learn cloud deployment on Azure, AWS, or GCP and DevOps practices (Docker, CI/CD).
- Commitment to responsible AI: reliability, security, and measurable business impact.
- Excellent communication and collaboration skills for cross‑functional team enablement.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Data Science, Engineering or related discipline.
- Certifications in cloud platforms (Azure AI, AWS AI, GCP AI) and/or MLOps, or equivalent professional experience.