- Company Name
- Xcede
- Job Title
- AI Engineer
- Job Description
-
**Job Title:** AI Engineer
**Role Summary:**
Design, build, and deploy practical AI solutions that drive personalization, automation, and user guidance within digital products. Focus on end‑to‑end machine learning workflows, LLM‑based tools, and scalable cloud deployment to power next‑generation user experiences.
**Expectations:**
- Deliver production‑ready AI features and models in a live product environment.
- Write clean, reproducible Python code using modern ML libraries.
- Experiment with LLMs, vector search, and prompt engineering while ensuring safety and accuracy.
- Operate within a cross‑functional team, translating product ideas into measurable AI outcomes.
- Maintain high engineering standards for model integration, quality assurance, and responsible AI practices.
**Key Responsibilities:**
1. Develop and launch intelligent features for personalization, automation, and user guidance across web and mobile platforms.
2. Build, test, and deploy machine‑learning pipelines and LLM‑powered applications (recommendation engines, assistants, data enrichment layers).
3. Prototype experimental AI solutions using LLM orchestration frameworks, vector search, and prompt engineering.
4. Collaborate with backend and infrastructure teams to support training pipelines, inference workflows, and scalable cloud‑native deployment.
5. Integrate third‑party data and tools via custom APIs and automation endpoints.
6. Contribute to internal frameworks for evaluating model performance, safety, and output consistency (prompt variation, A/B testing).
7. Drive raise of engineering standards around model integration, QA, and responsible development.
**Required Skills:**
- Proficient in Python, with experience in PyTorch, TensorFlow, Hugging Face, or similar libraries.
- Hands‑on with LLM systems (structured generation, retrieval‑augmented generation, embeddings).
- Understanding of model testing/validation workflows: prompt evaluation, fine‑tuning, A/B testing.
- API development and integration into production services.
- Cloud familiarity (Azure, GCP, AWS) and experience with scalable, reproducible ML deployments.
- Knowledge of vector/search technologies and prompt engineering techniques.
- Strong collaboration and communication skills; ability to balance experimentation with production robustness.
- Adherence to responsible AI and quality engineering best practices.
**Required Education & Certifications:**
- Bachelor’s degree (or higher) in Computer Science, Data Science, Electrical Engineering, or closely related field, or equivalent professional experience.
- AI/ML certifications (e.g., Google Cloud ML, AWS Certified Machine Learning, Azure AI Engineer) are a plus but not mandatory.