> Djinni

AI Engineer

pythonangularllmlangchainlanggraphmcpprompt engineeringopenaiopenshiftkubernetesdockergitlab ci/cdhelmpostgresqlrest-apijiraconfluence

domainFintech

> full description

This is not a traditional fullstack development assignment. Client requires specialists capable of combining established software engineering practices with the design, integration and optimisation of AI-powered functionalities within business-critical banking applications.

The candidates will initially support the maintenance, stability and continuous improvement of existing applications. Over time, they will progressively assume full responsibility for implementing new functionality and translating business requirements into production-ready solutions.

Key responsibilities:
1. Maintain, troubleshoot and continuously improve existing applications and services to ensure stability, performance and reliability.
2. Independently analyse business requirements, design solutions and implement new application features and enhancements.
3. Contribute to the design, development and continuous improvement of AI-powered application functionalities.
4. Support the architecture and implementation of intelligent chatbot solutions powered by Large Language Models.
5. Develop and integrate application interfaces to enable reliable communication between internal systems, external platforms and AI services.
6. Participate in architectural decisions concerning application scalability, infrastructure, maintainability and security.
7. Support deployment, operation and optimisation of applications within cloud-native and containerised environments.
8. Collaborate closely with developers, architects, business stakeholders and other cross-functional team members.
9. Work within an Agile/Scrum environment, participating in planning, refinement, implementation and delivery activities.
10. Apply secure development practices, including protection against misuse, inappropriate content and unauthorised access.
11. Ensure that implemented solutio

Must-haves:
1. Python development: Strong professional experience developing, maintaining and optimising backend services using Python. Candidates must be capable of independently implementing complex business logic and delivering reliable, maintainable applications.

2. Angular 21+: Hands-on experience developing modern frontend applications using Angular version 21 or newer, including implementing new features, maintaining existing components and integrating frontend applications with backend services.

3. Fullstack software engineering: Proven ability to work across frontend and backend components, understand end-to-end application architecture and deliver complete functional solutions.

4. AI and LLM integration: Practical experience designing, developing and integrating AI-powered application components, particularly solutions based on Large Language Models.

5. LangChain and LangGraph: Hands-on experience with both frameworks to develop, orchestrate and manage LLM-driven workflows, application logic and AI-based interactions.

6. MCP and A2A: Practical experience with Model Context Protocol (MCP) and Agent-to-Agent (A2A) technologies for connecting AI systems, external tools and agent-based functionalities.

7. LLM chatbot development: Experience designing and implementing LLM-powered chatbot solutions, including conversation handling, integration with existing systems and production deployment.

8. Prompt Engineering: Ability to design, structure, test and optimise prompts to improve the quality, consistency, reliability and relevance of AI-generated responses.

9. OpenAI integration: Experience integrating OpenAI or comparable AI platforms into software applications through APIs and related integration mechanisms.

10. AI solution architecture: Understanding of architectural patterns for building secure, reliable, scalable and maintainable AI-powered software solutions.

11. Containerisation and orchestration: Practical experience with OpenShift, Kubernetes and Docker for deploying, managing and maintaining containerised applications.

12. GitLab and Helm: Experience using GitLab within software development workflows and Helm for managing application deployments in Kubernetes environments.

13. PostgreSQL: Experience working with PostgreSQL databases, including application integration, data persistence and database-related development activities.

14. REST API development: Strong experience designing, developing, integrating and maintaining REST APIs and other application interfaces.

15. Network infrastructure and security: Good understanding of networking principles, infrastructure components, secure communication and relevant application security concepts.

16. AI application security: Experience implementing security and protection mechanisms, specifically:
- Rate limiting to control request volumes and prevent misuse.
- Spam protection to reduce malicious or unwanted interactions.
- Guardrails to control AI behaviour and enforce application policies.
- Content filtering to prevent inappropriate or prohibited outputs.
- Content moderation to identify and manage potentially harmful user inputs and AI-generated content.
17. Agile/Scrum: Practical experience working within Agile software development teams, including sprint planning, collaboration, iterative delivery and continuous improvement.

18. Jira and Confluence: Experience using Jira for task and project tracking and Confluence for technical documentation and knowledge sharing.

19. Independent delivery: Ability to transition from supporting maintenance activities to independently owning the implementation of new features and business requirements.