- Company Name
- Amazech Solutions
- Job Title
- Artificial Intelligence Engineer
- Job Description
-
Job title: Artificial Intelligence Engineer
Role Summary: Design, prototype, and deploy generative AI solutions across cloud and on‑prem environments, driving rapid experimentation and production readiness for complex language models and retrieval-augmented systems.
Expactations: Deliver end‑to‑end AI prototypes that validate business value, integrate with existing infrastructure, and meet performance, safety, and compliance standards. Collaborate with cross‑functional teams to define problem scopes, evaluate model behavior, and iterate solutions that scale.
Key Responsibilities:
- Build and evaluate large‑language‑model (LLM) workflows, prompt engineering and retrieval‑augmented generation (RAG) pipelines using LangChain, LangSmith, CrewAI, or equivalent.
- Develop rapid proof‑of‑concepts for new AI use cases, translating research prototypes into production‑ready code.
- Tune model hyperparameters, benchmark outputs, and set up evaluation frameworks for metrics such as relevance, safety, and latency.
- Integrate AI services through APIs (OpenAI, Anthropic, Hugging Face, Azure AI, AWS Bedrock, etc.) into broader MLOps pipelines.
- Maintain vector databases, knowledge bases, and data ingestion workflows; ensure data quality and compliance.
- Collaborate with developers, data engineers, and product owners to define AI requirements, roadmaps, and deployment schedules.
Required Skills:
- 5+ years in AI/ML engineering, research roles, or prototyping positions.
- Advanced Python programming; proficiency with TensorFlow, PyTorch, and additional ML libraries.
- Deep experience with LLMs, prompt engineering, RAG systems, LangChain, LangSmith, CrewAI, and vector database technologies.
- Practical knowledge of AI ecosystems (OpenAI, Anthropic, Hugging Face, Azure AI, AWS Bedrock).
- Familiarity with MLOps tools, GitHub Copilot, GPT-based coding assistants, and CI/CD pipelines for AI models.
- Strong analytical, debugging, and documentation skills; ability to explain complex model behavior to non‑technical stakeholders.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or related field (master’s preferred).
- Industry certifications in machine learning, AI, or cloud AI services (e.g., TensorFlow Professional, AWS Machine Learning Specialty) are a plus.