About the project
We are supporting a large-scale modernization program for a leading financial services organization, bringing together Generative AI, legacy/mainframe modernization, cloud transformation, data migration, and modern software architecture.
The AI stream focuses on using GenAI, LLMs and agentic solutions to accelerate legacy modernization, including automated code analysis, business rule extraction, reverse engineering, source-to-target conversion, and automated test generation.
The project offers the opportunity to work on complex enterprise-scale transformation initiatives, combining hands-on AI engineering with modern architecture and legacy system modernization.
Project details:
Industry: Financial Services
Location: Remote
Duration: 9–12 months
Start: ASAP / by agreement
Your responsibilities
- Lead the technical delivery of GenAI modernization solutions.
- Design LLM and RAG architectures for enterprise use cases.
- Design and implement Agentic AI solutions and workflows.
- Define AI solution architecture, technical standards and integration patterns.
- Lead development of AI-assisted code analysis and legacy modernization tools.
- Support legacy system reverse engineering using AI-based approaches.
- Develop solutions for business rule extraction from legacy systems and source code.
- Oversee the development of AI modernization accelerators and automation frameworks.
- Guide AI Engineers in the implementation of Python-based GenAI solutions.
- Evaluate and select appropriate LLM models, frameworks and vector databases.
- Ensure scalability, security, reliability and maintainability of enterprise AI solutions.
Our requirements
- Proven experience in technical leadership of AI/GenAI projects.
- Strong hands-on experience with Generative AI and LLMs.
- Strong knowledge of LLM architecture, RAG and Prompt Engineering.
- Practical experience with Agentic AI / AI Agents.
- Strong Python development skills.
- Experience with LangChain and/or LlamaIndex.
- Experience with OpenAI models and Azure AI Services.
- Experience working with vector databases and embeddings.
- Experience with legacy system modernization or software transformation.
- Strong understanding of enterprise and solution architecture.
- Ability to lead technical teams while remaining hands-on.
What we offer
- Duration: 9–12 months
- Workload: Full-time
- Start: As soon as possible / by agreement
- 100% remote
- Medicover
- Medicover Sport