Senior Ai/Agentic AI Developer - Dataiku Platform

About the job

Role Purpose

We are looking for experienced AI and Dataiku SMEs to support the design, development, and delivery of advanced AI use cases, including Agentic AI solutions, machine learning workflows, LLM-powered applications, data pipelines, and AI automation capabilities.

The selected candidates should have hands-on experience in developing AI solutions using the Dataiku platform, with strong technical knowledge in data engineering, machine learning, LLM integration, workflow orchestration, and production-ready AI use case implementation.

Key Responsibilities

1. Develop AI and Agentic AI use cases

• Design, build, and deploy AI/ML use cases using Dataiku.
• Develop Agentic AI workflows, including multi-step reasoning, task orchestration, tool usage, and

human-in-the-loop interactions.

• Build LLM-powered solutions such as intelligent assistants, document analysis, classification,

summarization, recommendation, and decision-support use cases.

2. Work on the Dataiku platform

• Develop projects, flows, recipes, scenarios, dashboards, and automation workflows in Dataiku.
• Use Dataiku for data preparation, feature engineering, model training, model evaluation, deployment, and monitoring.
• Support the configuration and usage of Dataiku advanced capabilities, including MLOps, model

governance, APIs, and AI/LLM features where applicable.

3. Develop data pipelines

• Build reliable and scalable data pipelines from multiple source systems.
• Perform data ingestion, transformation, cleansing, validation, enrichment, and integration.
• Work with structured and unstructured data, including databases, files, APIs, logs, documents, and external data sources.

4. Machine learning and analytics development

• Develop supervised and unsupervised ML models.
• Apply predictive analytics, classification, clustering, anomaly detection, NLP, and advanced analytics techniques.
• Evaluate model performance and optimize models for accuracy, reliability, and business value.

5. LLM and GenAI implementation

• Integrate Large Language Models with enterprise data and workflows.
• Develop prompt engineering, RAG pipelines, embeddings, vector search, and document intelligence use cases.
• Support secure and governed usage of GenAI within enterprise environments.

6. Deployment and productionization

• Package AI use cases for deployment into production environments.
• Build APIs, batch jobs, automated workflows, and reusable components.
• Support performance tuning, monitoring, testing, and documentation.

7. Collaboration and knowledge transfer

• Work closely with the company business SMEs, data teams, IT teams, and governance teams.
• Translate business requirements into technical AI solutions.
• Prepare technical documentation, solution designs, and implementation guides.
• Provide knowledge transfer and enablement to internal teams.

Required Experience

• 5+ years of experience in AI, machine learning, data science, or data engineering.

• 2+ years of hands-on experience with Dataiku platform.

• Proven experience developing AI use cases from concept to implementation.

• Experience with Agentic AI, GenAI, LLM applications, or AI workflow orchestration.

• Strong experience in developing data pipelines and data transformation workflows.

• Strong Python development skills.

• Experience working with SQL and relational databases.

• Experience integrating APIs, enterprise systems, and external data sources.

• Experience with MLOps, model deployment, model monitoring, and AI governance is preferred.

• Experience in government, tax, financial services, public sector, or regulated environments is an advantage.

Required Technical Skills

• Dataiku DSS

• Python

• SQL

• Machine Learning

• Data Engineering

• Data Pipelines / ETL / ELT

• APIs and system integration

• LLMs and Generative AI

• Prompt engineering

• RAG pipelines

• Embeddings and vector databases

• NLP and document intelligence

• Model deployment and monitoring

• MLOps and AI lifecycle management

• Git / DevOps practices

• Cloud or on-premise AI deployment environments

Preferred Dataiku Capabilities

• Dataiku Flows and Recipes

• Visual and code-based recipes

• Scenarios and automation

• Dataiku APIs

• Model training and AutoML

• Model deployment

• Feature engineering

• Data quality and preparation

• MLOps and model governance

• LLM integration and GenAI capabilities

• Dataiku governed AI / responsible AI features

• Dataiku dashboards and reporting

Preferred Profile

• A hands-on developer.
• Able to independently build working AI prototypes and production-ready solutions.
• Comfortable working with business users and technical teams.
• Strong in problem-solving and translating business needs into AI use cases.
• Familiar with enterprise security, governance, and compliance requirements.
• Able to work under tight timelines and deliver practical results.
• Able to operate within a government and regulated environment such as the company.

Deliverables Expected

• AI/ML use case prototypes and production solutions.
• Agentic AI workflows and solution components.
• Data pipelines and integrated datasets.
• Dataiku projects, flows, recipes, scenarios, and dashboards.
• LLM/RAG-based applications.
• APIs or integration components.
• Technical documentation and solution design.
• Deployment and operational support documentation.
• Knowledge transfer sessions for the company internal teams.

Minimum Qualifications

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering,

Information Systems, or related field.

• Relevant certifications in Dataiku, AI/ML, cloud, data engineering, or GenAI are preferred

Requirements added by the job poster

• 5+ years of work experience with Agentic AI Development
• 5+ years of work experience with Dataiku DSS
• 5+ years of work experience with Artificial Intelligence (AI)