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.

Experience
2-6 yrs