- Company Name
- Glue Reply
- Job Title
- Lead Engineer
- Job Description
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**Job title:** Lead Engineer – AI Engineering Lead
**Role Summary:**
Lead AI Engineering initiatives, guiding a multidisciplinary team in the design, development, and deployment of AI solutions. Oversee end-to-end project delivery, ensuring best practices, scalability, and alignment with stakeholder objectives.
**Expectations:**
- Deliver high‑quality AI models and systems on schedule and within scope.
- Foster a culture of continuous improvement, innovation, and technical excellence.
- Communicate complex technical concepts to non‑technical stakeholders and drive consensus.
**Key Responsibilities:**
- Architect and implement end‑to‑end AI pipelines, from data ingestion and feature engineering to model training, validation, and production deployment.
- Champion model testing, monitoring, and retraining strategies to maintain performance over time.
- Lead, mentor, and grow a team of AI/ML engineers, data scientists, and data engineers.
- Own project lifecycle: scoping, requirements definition, resource allocation, risk assessment, and status reporting.
- Integrate AI solutions with existing enterprise systems and infrastructure.
- Apply agile methodologies (Scrum/Kanban) to optimize workflow and delivery cadence.
- Ensure compliance with data privacy, security, and industry standards.
- Collaborate with product, business, and client teams to translate insights into actionable outcomes.
**Required Skills:**
- Advanced proficiency in AI/ML algorithms, model development, and statistical learning techniques.
- Expertise in data engineering, ETL processes, and data visualization.
- Strong programming skills in Python, Java, and R; experience with relevant ML frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn).
- Proven project management and team leadership experience.
- Familiarity with agile practices and CI/CD pipelines for ML.
- Excellent analytical, problem‑solving, and decision‑making capabilities.
- Effective written and verbal communication; ability to present technical findings to diverse audiences.
**Required Education & Certifications:**
- Master’s or Ph.D. in Computer Science, Engineering or a closely related technical field.
- Professional certifications in AI/ML, data science, or project management preferred but not mandatory.
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