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AI Engineer
Job Location:
Salary:
Experience Required:
Posted:
31 August 2026 (15 hours ago)
Posted:
Application Deadline:
28 November 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Company Overview
Jetbro is a technology partner for enterprises where reliability is non-negotiable. We build and integrate mission-critical systems across technology consulting engineering data cloud and AI. Our operating principle is Function over flash. Always. We favour practical resilient engineering and solutions designed for long-term clarity scale and business impact.
The selected candidate will be employed by Safal Softcom (Jetbros Partner company) and work on-site from Safal Softcoms premises embedded within its product team. SAFAL is an AI-powered Source-to-Pay platform for industrial enterprises supporting complex high-volume business-critical procurement operations across areas including sourcing supplier management contracts purchasing invoicing and spend intelligence.
About the Role
We are seeking an AI Engineer with 13 years of experience to join a 20-person B2B product this full-time on-site role you will help develop and productionise intelligent features for enterprise procurement workflows. Your work will support practical use cases including supplier scoring spend analytics forecasting recommendations document intelligence anomaly detection and workflow automation.
You will bridge research and engineering: evaluating suitable AI/ML techniques training and fine-tuning models and integrating dependable AI services into the product. You will collaborate closely with backend engineers frontend engineers product managers and domain specialists to ensure each solution is accurate scalable explainable and valuable to users.
Key Responsibilities
- Research and evaluate AI/ML techniques relevant to procurement workflows including forecasting recommendations document intelligence and anomaly detection.
- Develop train evaluate and fine-tune models for use cases such as supplier scoring spend analytics and anomaly detection.
- Prepare high-quality datasets for training and testing through cleaning structuring validation and feature engineering.
- Build and integrate AI services into the product in collaboration with backend and frontend engineering teams.
- Translate product requirements and domain needs into well-defined experiments technical approaches and measurable model objectives.
- Conduct experiments benchmark models against suitable baselines and communicate findings to support evidence-based decisions.
- Optimise deployed models for accuracy latency reliability scalability and operational performance.
- Explore and implement agentic AI workflows that automate multi-step procurement tasks and support informed decision-making.
- Develop APIs or services that expose model capabilities reliably and securely to other parts of the platform.
- Monitor model and data performance after deployment investigate degradation and implement appropriate improvements.
- Maintain clear documentation for research datasets experiments model behaviour evaluation results and implementations.
- Participate in code reviews contribute to high engineering standards and improve the reproducibility and maintainability of AI systems.
Requirements
Mandatory Requirements
- 24 years of professional experience in AI engineering machine learning data science or a closely related role.
- Strong proficiency in Python and experience with ML libraries such as scikit-learn XGBoost LightGBM or comparable tools.
- Sound understanding of machine learning fundamentals including supervised and unsupervised learning feature engineering overfitting validation and evaluation metrics.
- Experience preparing and analysing data with pandas NumPy or similar libraries.
- Familiarity with model-training workflows hyperparameter tuning cross-validation and experiment tracking.
- Ability to prepare reliable training and test datasets including data cleaning structuring validation and quality checks.
- Working knowledge of SQL for querying and analysing data.
- Foundational understanding of model deployment inference API integration and production performance considerations.
- Experience using Git and working effectively within collaborative software-development workflows.
- Ability to write clean maintainable well-documented and testable code.
- Strong analytical and problem-solving skills including the ability to investigate complex data or model issues.
- Full-time availability and willingness to work on-site from Safal Softcoms premises as an embedded member of the product team.
What we care about
- Function over flash. We value straightforward well-reasoned solutions that solve real problems over unnecessary complexity or novelty.
- Reliability and reproducibility. Models must be well tested documented traceable and dependable in production.
- Ownership. You will take responsibility for the quality and lifecycle of your work from research and implementation to deployment and improvement.
- Business impact. We prioritise AI features that create measurable value for enterprise users and improve real procurement decisions or processes.
- Collaboration. Clear communication and productive teamwork across product engineering and domain teams are essential.
- Learning mindset. AI evolves quickly; we value people who remain curious learn from experiments and apply new knowledge thoughtfully.
- Scalability. You will consider data quality cost latency model serving and long-term maintenance from the beginning.
About You
You are an early-career AI engineer with a strong grounding in machine learning and an interest in applying it to complex real-world business problems. You enjoy moving between data experiments code and product requirements and you care as much about production usefulness as model performance.
You take a pragmatic approach to problem-solving. You understand that a model is only valuable when it can be deployed monitored understood by stakeholders and maintained over time. You can balance accuracy simplicity explainability and operational constraints without losing sight of the user and the business outcome.
You communicate clearly welcome feedback and enjoy working closely with engineers and non-technical colleagues. You are comfortable working through ambiguity breaking large problems into manageable experiments and building dependable systems within a collaborative product team.
Benefits
Growth at Jetbro
If you do well this role can grow into:
- Senior Backend Engineer
- Platform / Infrastructure Engineer
- System Architect (longer term)
We invest heavily in people who invest in learning.
Required Skills:
24 years of professional experience in AI engineering machine learning data science or a closely related role. Strong proficiency in Python and experience with ML libraries such as scikit-learn XGBoost LightGBM or comparable tools. Sound understanding of machine learning fundamentals including supervised and unsupervised learning feature engineering overfitting validation and evaluation metrics. Experience preparing and analysing data with pandas NumPy or similar libraries. Familiarity with model-training workflows hyperparameter tuning cross-validation and experiment tracking. Ability to prepare reliable training and test datasets including data cleaning structuring validation and quality checks. Working knowledge of SQL for querying and analysing data. Foundational understanding of model deployment inference API integration and production performance considerations. Experience using Git and working effectively within collaborative software-development workflows. Ability to write clean maintainable well-documented and testable code. Strong analytical and problem-solving skills including the ability to investigate complex data or model issues. Full-time availability and willingness to work on-site from Safal Softcoms premises as an embedded member of the product team.
Required Education:
Graduate or Post-Graduate
