- Company Name
- fifty-five
- Job Title
- AI Engineer (H/F)
- Job Description
-
**Job Title:** AI Engineer
**Role Summary:**
Design, develop, and industrialize advanced generative AI solutions—including Retrieval‑Augmented Generation (RAG), autonomous/multi‑agent systems, reasoning, and tool‑calling—within a global data‑focused consultancy. Ensure robust, secure, and scalable production deployment, integrate AI components into existing data ecosystems, and uphold engineering best practices.
**Expectations:**
- Deliver high‑quality, production‑ready AI systems that meet performance, cost, and security targets.
- Operate effectively in a fast‑paced, multi‑disciplinary, multicultural environment.
- Communicate complex technical concepts clearly to non‑technical stakeholders.
- Exhibit strong software‑engineering discipline, agility, and continuous learning.
**Key Responsibilities:**
1. **AI Solution Development**
- Architect and implement generative AI models (RAG, autonomous agents, multi‑agent coordination).
- Build and optimize knowledge bases, ingestion pipelines, chunking, and embedding processes.
- Conduct advanced prompt engineering and model‑application interaction design.
- Convert PoCs into production‑grade, maintainable systems.
2. **Industrialization & MLOps**
- Scale AI services for high user load; manage cloud and DevOps deployments.
- Monitor and reduce inference costs (token usage) while maintaining latency and quality.
- Implement supervision tools (quality metrics, drift detection, RAGAS) and perform ongoing maintenance.
3. **Technical Quality Assurance**
- Write robust, well‑tested code adhering to software‑engineering standards.
- Ensure AI security, compliance, and governance in partnership with dedicated teams.
- Document architecture, pipelines, and best‑practice guidelines.
4. **Ecosystem Integration**
- Seamlessly integrate AI components with existing data, IT, security, and product platforms.
- Collaborate with cross‑functional teams to guarantee solution coherence and performance.
**Required Skills:**
- Expert‑level Python programming.
- Deep knowledge of generative AI, large language models (LLMs), and prompt engineering.
- Proficiency with LangChain, agent orchestration, vector databases, and LangGraph.
- Experience consuming LLM APIs (e.g., Vertex AI, Azure OpenAI).
- Strong software‑engineering foundation: system architecture, unit/integration testing, CI/CD, coding standards.
- Good understanding of cloud platforms (AWS, GCP, Azure) and DevOps practices.
- Agile mindset, rigor, curiosity, and rapid adaptation to complex technical settings.
- Excellent collaboration skills and ability to explain technical topics to non‑experts.
**Required Education & Certifications:**
- Bachelor’s (minimum) or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related quantitative field.
- Relevant certifications (e.g., Cloud Provider AI/ML certifications, MLOps certifications) are a plus but not mandatory.