Software Development Engineer - AI

Responsibilities:

• Developing, designing, and demonstrating new features and components of the back end to users to ensure compliance with requirements
• Assisting in the design, implementation and optimisation of related approaches, tools and workflows.
• Collaborate with the technical teams, business teams, and product managers to ensure that the code that is developed meets their vision.
• Develop and integrate AI-enabled capabilities leveraging approved enterprise AI services and APIs.
• Contribute to AI-powered application features such as intelligent search, conversational interfaces, recommendation engines, and workflow automation.
• Follow Responsible AI principles to ensure fairness, transparency, privacy, explainability, and accountability in AI-enabled solutions.
• Develop the solutions to meet functional and technical requirements.
• Align to Security/Compliance frameworks and control requirements.
• Own quality posture. Write automated tests, ideally before writing code.
• Write well-designed, non-complex, testable, efficient code.
• Develop Continuous Integration and Continuous Deployment pipelines and automated deployment scripts.
• Configure services, such as databases and monitoring.
• Implement Service Reliability Engineering.
• Fix problems from the development phase through the production phase, which requires being on call for production support.
• Design and implement microservices-based architecture.
• Develop REST APIs and document them using Swagger/OpenAPI.
• Build and deploy serverless and containerised microservices in cloud environments.
• Monitor and troubleshoot applications using CloudWatch, Sumo Logic, and Dynatrace.

Requirements:

• Hands-on experience in software development in Java, Microservices, REST APIs, Monitoring, AWS, AI, and relational and NoSQL databases.
• Work with frameworks such as Spring Boot, Quarkus, Hibernate.
• Understanding of Generative AI concepts, Large Language Models (LLMs), embeddings, vector databases, and Retrieval Augmented Generation (RAG) patterns.
• Experience integrating AI capabilities into enterprise applications using AI APIs, SDKs, or cloud-based AI services.
• Good with prompt engineering techniques and AI-assisted software development tools.
• Knowledge of AI agent concepts, AI orchestration frameworks, and intelligent workflow automation.
• Understanding of ontology, metadata, semantic models, knowledge graphs, or enterprise knowledge management concepts.
• Understanding of Responsible AI principles including fairness, transparency, explainability, privacy, and accountability.
• Knowledge of AI security risks including prompt injection, data leakage, adversarial inputs, model misuse, and secure AI application development practices.
• Ability to implement AI guardrails, content filtering, and monitoring controls within AI-enabled solutions.
• Familiarity with AWS AI/ML services such as Amazon SageMaker, Bedrock, and AgentCore.
• Understanding of LLM-based solutions is highly desirable.
• Good judgment and problem-solving skills with the ability to resolve issues calmly and effectively.
• Expert in Functional Programming approaches, mostly in Java 21
• Experience working with containerization technologies.
• In-depth working knowledge of Lambda, EC2 S3 and container services, etc.
• Knowledge of Authentication and Authorisation protocols like OAuth 2.0 and OpenID Connect, etc.
• Excellent judgment and problem-solving skills; individuals should be able to resolve problems in a calm and quick manner and display a high degree of initiative and drive.
• Professional experience working with Agile Methodologies is required.
• Experience working with DevOps principles, practices and tools in an enterprise technology environment is required.
• Experience of engineering software within an Amazon Web Services (AWS) cloud infrastructure or other prominent enterprise cloud provider is required.
• Working knowledge of the full Software Development Lifecycle, building CI/CD pipelines and practising Test Driven Development is a requirement.
• Leverage AI tools (e. g., Kiro/Kiro CLI) for generation, debugging and building simple AI-driven features.
• Experience with source control, build tools and GIT (GitHub, Bitbucket or other) is required.
• Embraces diverse people, thinking and styles.
• Consistently makes the safety and security of self and others the priority.
• High School diploma, GED or High School Equivalency.