SDE III - Backend
Job location: Remote
About the role:
The Senior Software Engineer - Backend will work as part of the Digitization and Automation team to design, develop, and implement scalable technology solutions that solve a wide variety of business problems across the organization. This role is primarily a backend engineering role, requiring strong software engineering fundamentals, system design expertise, and ownership of business-critical applications. In addition, the engineer will play a key role in identifying, designing, and building AI-powered solutions that improve operational efficiency, automation, decision-making, and developer productivity across the organization. The ideal candidate combines strong backend engineering experience with practical experience building AI-powered applications, agents, copilots, retrieval systems, and workflow automations. They should be comfortable evaluating where AI adds value, designing appropriate system architectures, and mentoring other engineers on AI-related engineering practices.
What you will be expected to do
- Design, build and integrate scalable and reliable backend systems based on business and product requirements.
- Identify and resolve bottlenecks, bugs, and operational issues.
- Drive improvements in scalability, performance, reliability, observability, and cost optimization.
- Create prototypes and proof-of-concepts for new products and features and do POC to validate new AI initiatives.
- Take complete ownership of projects from design through deployment and production support.
- Collaborate closely with Product Managers, Business Analysts, QA teams, and other engineering teams.
- Lead the establishment and evolution of Sun King 's AI Engineering capabilities, including architecture, tooling, development standards, and best practices.
- Define and drive the AI technology stack, ensuring scalable, secure, reliable, and cost-effective adoption of AI across engineering and business workflows.
- Architect systems that combine LLMs, retrieval systems, business logic, databases, APIs, and operational tooling.
- Evaluate emerging AI technologies, frameworks, and models, and provide technical direction on their adoption and integration within the organization.
- Mentor and guide engineers on backend architecture, AI system design, and implementation best practices, fostering AI expertise across the team.
Good to Have
- Experience with messaging systems such as RabbitMQ, Kafka, or Amazon SQS.
- Experience with containerized deployments using Docker and Kubernetes.
- Experience building retrieval systems, semantic search, or knowledge assistants.
- Familiarity with agent frameworks and orchestration platforms.
- Experience integrating AI systems with enterprise applications, operational tooling, or internal platforms.
- Experience working with vector databases and embeddings.
- Experience building internal developer productivity or operational automation tools.
- Exposure to Model Context Protocol (MCP) or similar tool integration patterns.
- Strong curiosity for emerging technologies and willingness to continuously learn and experiment.
You might be a strong candidate if you have/are
- Strong experience in designing and developing scalable REST-based micro-services and APIs using Java (Spring Boot) and Python.
- Strong experience with SQL, database design, and query optimization.
- Experience working with AWS services such as EC2, RDS and Lambda.
- Hands-on experience building AI-powered applications or workflows in production environments.
- Practical understanding of Retrieval-Augmented Generation (RAG) architectures and their application to business problems.
- Experience designing and building AI agents, copilots, workflow assistants, or intelligent automation systems.
- Understanding of tool-calling, context management, prompt design, structured outputs, and hallucination mitigation techniques when integrating LLMs with business Systems, APIs and