Tasks and responsibilities

AI Solutions Specialist:
•    Gather and analyse business requirements from stakeholders and translate them into technical specifications.
•    Collaborate with cross-functional teams to ensure alignment of AI projects with business goals, facilitating communication between technical and non-technical stakeholders.
•    Develop and maintain documentation, including business cases, process flows, and user stories.
•    Design and develop full-stack AI systems, leveraging AI/ML services
•    Develop solutions following CI/CD best practices
•    Assemble, extend and integrate AI-based automation and knowledge solutions leveraging low-code platforms

Data Science and ML Specialist:
•    Design and implement ETL processes to integrate data from various sources.
•    Build and maintain data pipelines to ensure data quality and accessibility.
•    Ensure data security and compliance with FAO data policies.
•    Develop and deploy machine learning models according to project requirements
•    Implement and maintain ML pipelines and workflows.
•    Optimize the use of LLMs for NLP use cases with best practices, including fine-tuning of Foundation Models
•    Monitor and evaluate model performance, making necessary adjustments.
•    Analyse large datasets to extract actionable insights, including structured statistical and geospatial
•    Build predictive models to support FAO’s decision-making processes.
•    Develop data visualization tools and dashboards to communicate findings.

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

Minimum Requirements

•    For COF: University degree in Information Technology or related discipline. Public Cloud (Azure, AWS, GCP or Microsoft PowerPlatform) professional certificates and 2 years of experience in full-stack software
•    For PSA: Relevant technical degree/certificate and at least than 1 year of experience in full-stack software development
•    For both COF and PSA: Additional 1+ years’ relevant experience with AI/ML services in multi-cloud environments and/or in Microsoft PowerPlatform and Copilot Studio environments
•    Working knowledge of English.

FAO Core Competencies

•    Results Focus
•    Teamwork
•    Communication
•    Building Effective Relationships
•    Knowledge Sharing and Continuous Improvement

Technical/Functional Skills 

AI Solutions Specialist:
•    Strong analytical and problem-solving skills with experience with requirements gathering and documentation.
•    Ability to translate business requirements into technical specifications and proficiency in business analysis tools and techniques (e.g., SWOT analysis, PEST analysis).
•    Deep understanding of AI technologies and their applications.
•    Experience with AI and LLM frameworks and cloud services (e.g., LangChain, LlamaIndex, AWS Bedrock, Azure AI/OpenAI, Vertex AI, Copilot Studio).
•    Proficiency in programming languages such as Python, JavaScript/TypeScript and familiarity with cloud platforms and services (e.g., AWS, GCP, Azure).
•    Experience in front-end technologies (e.g., HTML, CSS, JavaScript/TypeScript, React, Angular).
•    Experience with back-end technologies (e.g., Node.js, Django, Ruby on Rails).
•    Familiarity with cloud platforms and services (e.g., AWS, GCP, Azure, PowerPlatform).
•    Proficiency in low-code platforms like Microsoft PowerAutomate and Copilot Studio/Copilot for M365
•    Experience with SharePoint environments development.
•    Strong understanding low-code applications performance and scalability.
•    Proficiency with CI/CD tools (e.g., GitHub Actions, Bitbucket Pipelines).
•    Understanding of automated cloud infrastructure management and infrastructure as code (e.g., AWS CDK, Terraform).
•    Experience in containerization and orchestration tools (e.g., Docker, Kubernetes).

Data Science and ML Specialist:
•    Proficiency in ETL processes and data pipeline design.
•    Proficiency in multiple database types (e.g, SQL, NoSQL, key-value, document-oriented, graph).
•    Experience with cloud data services (e.g., BigQuery, AWS Glue).
•    Strong understanding of data preprocessing and feature engineering.
•    Proficiency in programming languages such as Python and ML frameworks like TensorFlow and PyTorch.
•    Familiarity with cloud-based ML platforms, pre-trained AI Models, NLP, Speech & Voice Services (e.g., SageMaker, Vertex AI, BigQuery ML, AutoML Azure ML. etc.).
•    Strong analytical skills.
•    Knowledge of machine learning algorithms and techniques.
•    Proficiency in programming languages such as R or Python and experience with data processing and visualization tools (e.g., Panda, Tableau, Power BI).