Your mission:
The Senior Applied AI Engineer will play a critical role in shaping Turaco’s AI-driven future, building intelligent systems that improve internal operations and deliver better outcomes for our customers and partners. This role sits within our “Service Center” team, supporting the operations and growth of multiple country offices.
You will partner with teams across technology, insurance operations, call center, partnerships, and business development to identify high-impact AI opportunities, ship production-grade solutions, and champion a culture of responsible, pragmatic AI use across the organization.
Key Roles & Responsibilities:
- Design, develop, and deploy AI/ML solutions that address real operational and customer-facing problems — from NLP and predictive models to LLM-powered workflows and intelligent automation.
- Translate business requirements into well-scoped AI projects with clear success metrics, timelines, and tradeoffs.
- Own the full ML lifecycle: data exploration, model development, evaluation, deployment, and monitoring.
- Build and maintain robust data pipelines and infrastructure to support model training and inference at scale.
- Lead and mentor a team of engineers, fostering growth through code reviews, pair programming, and knowledge-sharing.
- Collaborate with operations and product teams to embed AI capabilities directly into workflows and products.
- Evaluate and integrate third-party AI tools, APIs, and foundation models (e.g. LLMs) where they offer clear value.
- Create clear technical documentation for both technical and non-technical audiences.
- Proactively monitor deployed models for drift, degradation, and bias, and implement corrective measures.
Key Qualifications & Your Profile
- Lives Turaco’s values – pushing boundaries, working with excellence, and a profound respect for the individual.
- 7+ years of professional software experience, with at least 3 years in applied AI/ML roles in production environments.
- Startup or entrepreneurial experience is highly desirable – you are comfortable with ambiguity and moving fast.
- Demonstrated strong programming skills in at least two of these languages: Java, Python, Go, or JavaScript; experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
- Hands-on experience with LLMs and generative AI – prompt engineering, fine-tuning, Reinforcement Learning (RL), RAG architectures, or building LLM-powered applications.
- Solid understanding of classical ML: supervised/unsupervised learning, model evaluation, and feature engineering.
- Experience with data infrastructure – SQL/NoSQL databases, data pipelines, and cloud platforms (AWS, GCP, or Azure).
- Familiarity with MLOps practices: experiment tracking, model versioning, CI/CD for ML, and monitoring in production.
- Strong communication skills, able to translate complex AI concepts clearly for non-technical stakeholders.
- Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or a related field; strong academic track record preferred.
- A creative, first-principles thinker who can identify where AI creates genuine value – and where it doesn’t.
- Excellent team player with strong organizational and leadership skills.