Senior Software Engineer, Sinch

• 5–8+ years of professional software engineering experience
• Strong backend and platform skills including distributed systems, microservices, event-driven architectures, event-sourcing systems and cloud-native design on AWS
• Experience with Kafka or other event-streaming platforms
• Expertise in Golang for building backend services; willingness to learn other languages/technologies as needed (Java, React)
• Solid experience with data modelling and persistence at scale, ideally with DynamoDB (partition/sort key design, GSIs/LSIs, capacity planning, and consistency trade-offs) or equivalent NoSQL experience
• Experience integrating with LLMs and vector databases in a backend or platform context
• Experience with AWS and operations including core AWS services (DynamoDB, EKS, etc.), Docker, Kubernetes, CI/CD, GitOps, infrastructure as code, and monitoring
• Ability to explain architectural trade-offs clearly, especially around storage, consistency, and throughput
• Strong engineering fundamentals including clean code, testing strategies, debugging production systems, and building reliable, long-lasting systems
• Experience using AI coding tools such as Copilot, Claude Code, Cursor, or similar, with an understanding of their benefits, risks, and best practices
• Ability to work autonomously, define scope, and deliver solutions independently; strong decision-making on prioritisation
• Strong communication skills with both technical and non-technical stakeholders
• Fluent in English

Desirable

• We are building the next generation of conversational AI infrastructure
• As a Senior Software Engineer on the Context Storage team, you will design, build, and own the core data platform that captures, persists, and serves conversational context to AI agents operating across SMS, WhatsApp, and voice at scale
• This is a zero to one opportunity to build a new platform from the ground up, working closely with all the teams belonging to the AI Agents domain
• You will work on complex problems with high autonomy as part of a small senior team with significant impact
• You will collaborate with Engineering Managers, Tech Leads, Product Managers, Domain Architects and cross-functional teams
• Design and build the event-driven pipelines that capture conversational and interaction events across channels and persist them into durable, queryable stores
• Own the data model and storage architecture that represents conversational context in DynamoDB, designed for fast, consistent, and cost-efficient access by AI agents
• Design system architecture and create technical proposals covering event ingestion, schema/table design, single-table vs. multi-table strategies, and read/write access patterns on DynamoDB
• Build event sourcing / CQRS-style systems that reconcile high-throughput event streams via Kafka with strongly consistent context reads
• Write production-grade Go services, including clean, maintainable code with tests and documentation; build systems that are observable, debuggable, and resilient
• Own the full lifecycle of the systems you build: design, deployment, monitoring, and on-call responsibilities
• Follow a build-ship-run approach
• Design APIs and data contracts that let AI agent platform teams retrieve relevant context efficiently, addressing challenges like data freshness, TTL/retention, partition key design, hot partitions, and query latency at scale
• Optimise DynamoDB capacity modes, indexing (GSIs/LSIs), and access patterns for cost, throughput, and latency as event volume and agent concurrency grow
• Contribute to engineering excellence through architecture discussions, code reviews, and standards definition
• Mentor team members and share knowledge
• Collaborate across teams with product and technical stakeholders, providing technical guidance on trade-offs between consistency, availability, and performance