- Company Name
- Forsyth Barnes
- Job Title
- AI Engineer (Ref: 193791)
- Job Description
-
Job Title: AI Engineer (Ref: 193791)
Role Summary:
Design, develop, and deploy AI‑powered conversational agents and automation systems for web, SaaS, and enterprise products. Apply NLP, LLMs, and machine learning to create scalable, human‑like interactions that enhance user experience and operational efficiency.
Expectations:
- Deliver high‑quality, production‑ready chatbots and automation tools aligned with business objectives.
- Maintain a continuous improvement cycle for model accuracy, performance, and scalability.
- Collaborate cross‑functionally with product, design, and engineering teams to integrate AI solutions seamlessly.
Key Responsibilities:
- Design, build, and launch chatbot products for websites and SaaS platforms.
- Develop conversational flows using NLP and LLMs (e.g., GPT, Rasa, Dialogflow).
- Create, tune, and deploy machine learning and NLU models; integrate via RESTful APIs.
- Preprocess and analyze structured and unstructured data for training and evaluation.
- Perform model testing, optimization, and fine‑tuning to meet KPIs.
- Document architecture, processes, and technical specifications for scalability.
- Research emerging AI/ML technologies (LLMs, speech‑to‑text, prompt engineering, autonomous agents) and recommend adoption.
- Ensure secure, compliant deployment on cloud or on‑premise environments.
Required Skills:
- Proficient in Python (Java experience a bonus).
- Strong foundation in Machine Learning, Deep Learning, and NLP.
- Hands‑on with TensorFlow, PyTorch, SpaCy, NLTK, Hugging Face, Rasa, or Dialogflow.
- Experience building and consuming RESTful APIs.
- Knowledge of data preprocessing, algorithms, and statistical analysis.
- Excellent analytical, problem‑solving, and creative thinking skills.
Preferred Skills:
- Experience with LLMs (GPT, Claude, Gemini) and prompt engineering.
- Voice‑based AI agent development.
- Cloud platform (AWS, Azure, GCP) familiarity.
- MLOps, CI/CD pipelines, containerisation (Docker, Kubernetes).
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Data Science, or related technical field (or equivalent professional experience).
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Google Cloud Professional Data Engineer) are advantageous but not mandatory.
West midlands, United kingdom
Hybrid
24-11-2025