Senior Backend Engineer
HybridCheltenham, England, United Kingdom
Job Summary
Build new backend processing systems powering Obsidian's core SaaS security platform for enterprises like Snowflake and T-Mobile. Maintain, improve, and evolve existing systems to ensure performance, resilience, and scalability while designing and implementing APIs and multithreaded applications. Collaborate with product and engineering teams to support key product themes, apply strong software engineering practices to requirements gathering and code reviews, and leverage AI tools to enhance development efficiency and build AI-ready systems. Work alongside a talented team in a hybrid environment with supported remote options in Cheltenham and Manchester.
Required Qualifications
- 5-7 years of experience in a software engineering role
- Proficiency in one or more modern programming languages such as Python, Go or SQL
- Experience building backend services, APIs, and multithreaded applications
- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes
- Strong knowledge of relational databases (e.g., Postgres)
- Experience collaborating in team environments and adapting to changing requirements
- Understanding of software design principles and engineering best practices
- Experience with cloud platforms (AWS, GCP), object storage (S3), or event/streaming systems (Kafka, Redis)
- Familiarity with Git for version control and deployment tooling such as GitLab CI/CD
- Leverage AI tools effectively to improve development efficiency and build AI-ready systems
- Proficient with AI-powered developer tools; able to critically evaluate and refine AI-generated outputs
- Strong understanding of core AI/ML concepts (LLMs, embeddings, vector databases, inference, evaluation)
- Experience integrating AI/ML APIs and building AI-ready data infrastructure (e.g., for RAG)
- Ensure data quality, governance, observability, reliability, security, and performance in AI-driven systems
Desired Qualifications
- Experience with system monitoring and observability tools such as Grafana, Prometheus, or similar platforms
- Understanding of quality engineering (QE) practices across development and testing lifecycles
- Exposure to large-scale distributed systems and performance optimisation
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