Data Scientist - Multi-Agent AI Systems at Capgemini Portugal

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

16 May, 26

Salary

0.0

Posted On

15 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Multi-Agent Systems, RAG, Chatbot Solutions, Prompt Engineering, Generative Models, LLMs, Fine-Tuning, Python, Knowledge Bases, Evaluation Frameworks, Software Engineering, Machine Learning, Artificial Intelligence, Vector Databases, Data Science

Industry

IT Services and IT Consulting

Description

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose. Your Role Design and develop generative AI–based multi‑agent systems that can collaborate, communicate, and coordinate to achieve complex objectives, and architect RAG‑driven chatbot solutions that leverage knowledge bases and external data sources. Create sophisticated prompt‑engineering strategies to optimize agent behavior and inter‑agent communication, while building, training, and fine‑tuning generative models for multi‑agent applications. Develop robust evaluation frameworks to measure and improve system performance, implement efficient knowledge‑sharing mechanisms between agents, and write clean, efficient, well‑documented Python for production‑ready AI systems. Collaborate with cross‑functional teams to integrate these systems into broader product ecosystems, and stay at the forefront of AI research to incorporate state‑of‑the‑art techniques into our solutions. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutionsorapplications. 1. Applies scientific methods to analyse and solve software engineering problems. 2. Heorshe is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance. 3. Hisorher work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers. 4. The software engineer builds skills and expertise of hisorher software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities. 5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.Your Profile The candidate should hold a Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with 4+ years of professional experience in data science or machine learning engineering and strong expertise in Python and core ML libraries. They must have demonstrated experience in developing and deploying generative AI models such as LLMs or diffusion models, along with proven capability in building RAG‑based systems and working with vector databases. The role requires a solid background in prompt engineering for large language models and hands‑on experience designing and implementing generative AI–based multi‑agent architectures. The candidate should possess excellent problem‑solving abilities with the capacity to optimize complex AI systems efficiently. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Responsibilities

The role involves designing and developing generative AI-based multi-agent systems capable of collaboration and coordination to achieve complex goals, alongside architecting RAG-driven chatbot solutions leveraging external data sources. Responsibilities also include creating prompt engineering strategies, building and fine-tuning generative models, developing evaluation frameworks, and writing production-ready Python code.