ai/ ml backend developer

At DIGITALL we don't just deliver technology – we deliver the future We are explorers, knowledge-hunters, tech geeks, problem solvers and game changers who want to inspire and be inspired. Our DIGITALL people are always one step forward: working with top-notch technologies, creating innovations ahead of the market trends, sharing the passion for discovering better ways.

As a human-centric organization, our teams are built on mutual respect and open communication, allowing everyone to be authentic, express ideas and unleash their potential. We are proud of our DIGITALL bright minds and never stop developing their skills to keep pushing boundaries together and do what we love.

DIGITALL operates globally with a team of 1300 experts in 16 locations across 8 countries.

Supporting the organizations roll out and implementation of advanced Artificial Intelligence (AI) solutions to meet business needs.

The ideal candidate should have a solid background in backend development, AI/ML orchestration, and data management, with hands-on experience in Generative AI and Agentic AI frameworks. They will be responsible for building REST APIs, managing data pipelines, and implementing AI/ML solutions such as retrieval-augmented generation (RAG), intent detection models, and autonomous AI agents to deliver intelligent, production-ready solutions.

Backend Development: Design, develop, and maintain REST APIs using Python to integrate AI/ML services.

• Agentic AI Development: Design and orchestrate AI agents capable of reasoning, planning, and executing multi-step tasks by integrating LLMs with APIs, tools, and data sources.

• AI/ML Orchestration: Implement and manage machine learning models, large language models (LLMs), Agentic AI workflows and AI orchestration using Python.

• Generative AI Solutions: Using Generative AI models for tasks like text generation, summarization, conversational AI, and content creation.

• Data Management: Work with structured databases (SQL), graph databases (e.g., CosmosDB), and unstructured data stores (e.g., Elasticsearch).
• RAG Implementation: Build retrieval-augmented generation (RAG) pipelines leveraging Azure AI Search, AWS OpenSearch, or other vector databases for contextual responses.
• Data Pipelines: Design and manage robust data ingestion and transformation pipelines to feed AI models.
• Intent Detection & NLU: Develop or integrate intent detection models and natural language understanding (NLU) solutions to enhance conversational AI.
• Prompt Engineering & Optimization: Create and optimize prompts for LLMs to improve response quality and reduce latency.
• AI Integration: Collaborate with frontend and product teams to embed Gen AI features into enterprise applications.

• Backend Development: Proficient in Python for building and maintaining scalable REST APIs, familiarity with integrating AI services.
• AI/ML Orchestration: Strong expertise in Python with a focus on machine learning, large language models (LLMs), AI orchestration.
• Agentic AI Expertise: Experience in building autonomous AI agents using frameworks like OpenAI Functions, or custom orchestration solutions to handle tool use and multi-step reasoning.
• Generative AI Expertise: Generative AI models (text generation, summarization, conversational AI) and applying prompt engineering techniques.
• Data Management: Solid understanding of structured (SQL), graph (CosmosDB), and unstructured (Elasticsearch) databases; ability to design efficient data access patterns for AI workloads.
• RAG Implementation: Proven experience implementing retrieval-augmented generation using Azure AI Search, AWS OpenSearch, or other vector databases.
• Data Pipelines: Hands-on experience building and managing data ingestion and transformation pipelines using Databricks, Azure Data Factory, or equivalent tools.
• Intent Detection & NLU: Skilled in developing or deploying intent detection models and natural language understanding (NLU) components for conversational AI applications.
• Experience working within Agile environments, particularly Scaled Agile Framework (SAFe), is advantageous
• Ability to manage multiple tasks and deliver solutions in a fast-paced, dynamic environment

All applications will be treated in strict confidentiality

Please note that only shortlisted candidates will be invited to an interview

All applications will be treated in strict confidentiality

Please note that only shortlisted candidates will be invited to an interview