Nortal helps governments, healthcare institutions, and businesses manage complex transformation initiatives through digital strategy, consulting, and technology services. Its work spans the public sector, healthcare, financial services, and telecommunications, with a focus on improving operational efficiency and the experience of people who use digital services. Nortal’s teams support organizations as they adapt to changing economic and technological conditions and turn large-scale challenges into practical digital solutions.
Senior Python AI Engineer
Build production RAG, retrieval, and evaluation systems as a Senior Python AI Engineer. Develop Python services and knowledge pipelines for Nortal’s global mining client.
Description
- Design end-to-end knowledge pipelines, from source discovery and extraction to metadata, chunking, and indexing.
- Build hybrid retrieval and RAG systems with provenance, citations, access controls, refresh, and lineage.
- Create reusable evaluation frameworks and test packs for RAG assistants, document processing, and tool-using AI agents.
- Develop test scenarios, regression cases, golden datasets, deterministic checks, targeted LLM judges, and release thresholds.
- Improve AI answer quality across the pipeline, including source data, indexing, ranking, grounding, prompts, orchestration, and model behaviour.
- Design for precision, with appropriate abstention and fallback mechanisms.
- Build and maintain Python backend services, APIs, and test harnesses for AI components.
- Use automated testing, version control, CI/CD, observability, telemetry, traceability, resilience, and cost and latency optimisation.
- Work with subject matter experts to define expected answers, evidence, authoritative sources, ambiguity, exceptions, out-of-scope cases, and safety boundaries.
- Develop reusable engineering patterns for retrieval, semantic metadata, evaluation, monitoring, and safe production AI operations.
Requirements
- Strong practical experience developing Python backends with FastAPI or a similar framework.
- Demonstrated experience designing and building APIs and integrating asynchronous or external services.
- Practical experience building and improving AI or generative AI solutions, especially retrieval and RAG, document understanding, or knowledge-intensive assistants.
- Strong grasp of information retrieval, embeddings, vector search, and hybrid search.
- Experience evaluating AI systems with benchmark or golden datasets, regression tests, error analysis, evaluation metrics or judges, and calibration with human reviewers or subject matter experts.
- Experience delivering reliable production software with thorough testing, debugging, observability, and CI/CD.
- Good understanding of data quality, metadata, provenance, and versioning.
- Ability to identify quality issues across the full AI pipeline.
- Strong communication skills, including explaining AI quality limits and technical trade-offs to technical and non-technical audiences.
- Upper-intermediate or higher spoken and written English.
- Experience with ontologies, taxonomies, or semantic knowledge artefacts is an advantage.
- Data Science or Machine Learning experience combined with strong software engineering skills is an advantage.
- Spanish or Portuguese language skills are an advantage.
Benefits
- 24 working days of paid vacation.
- 11 paid national holidays.
- Up to 10 paid sick days.
- On-demand medical insurance.
- Vaccinations.
- Mental health support, including webinars, resources, and therapy session compensation.
- Access to a corporate learning platform.
- English classes.
- Flexible benefits budget for medical insurance, sports, leisure, fuel, and more.
- Eight-hour workday aligned with the client’s working hours.
- Hybrid work, with work-from-home options and office access.
- Team events and thoughtful gifts throughout the year.