Jobs at Version 1

Design, build, and operate backend services and REST APIs that integrate LLM/RAG features via AWS Bedrock, AgentCore, and SageMaker. Implement data models, CI/CD, automated tests, observability, AuthN/AuthZ, and performance tuning. Collaborate cross-stack with product, AI platform, and data teams to ship production AI-powered features and resolve latency, reliability, and data-quality issues.

Design, build, and operate scalable cloud‑native data platforms and reliable ETL/ELT pipelines (batch and streaming). Optimize performance, ensure production readiness (security, testing, observability), troubleshoot/operate systems, collaborate with analytics/AI teams, and mentor junior engineers to deliver enterprise data solutions.

Lead the delivery of data engineering projects by designing and building scalable data platforms; mentor engineers and ensure high-quality outcomes.

Design, build, and operate cloud-native data platforms and reliable ETL/ELT pipelines (batch and streaming) using Databricks and Spark on AWS/Azure. Ensure production readiness—security, testing, monitoring, cost efficiency—and optimise performance, reliability, and data quality. Collaborate with analysts, data scientists and platform teams, mentor junior engineers, support production troubleshooting, and contribute to technical design and operational standards.

Design, build, and ship production-grade AI products end-to-end: React frontends, Python backends integrating LLMs/agentic workflows, data layers (Postgres, Databricks, Redis), and CI/CD deployments on AWS (Bedrock, SageMaker) using Kubernetes and Terraform. Harden prototypes for security, scalability, observability, and mentor teams on best practices.