Sr. Software Engineer (Backend)

Role Overview :

We are looking for a Sr. Software Engineer to join our Core Integrations team. You will design, build, and scale the integration platform that connects our product ecosystem with third-party systems and you will do it with AI as a first-class tool throughout your workflow.

Core Technical Requirements :

• Java (Advanced): 6+ years of production Java experience. Deep knowledge of JVM internals, concurrency, memory management, and the Java ecosystem (Spring Boot, Hibernate, Maven/Gradle). Comfortable writing idiomatic, performant, maintainable Java code without hand-holding.
• Integration Patterns: Solid understanding of REST, GraphQL, gRPC, webhooks, event-driven architecture (Kafka, SQS, etc.), and common data formats (JSON, XML, Avro, Protobuf). Experience building and maintaining APIs consumed by external partners.
• Distributed Systems: Working knowledge of microservice design, fault tolerance patterns (circuit breakers, retries, idempotency), and observability (structured logging, tracing, metrics).
• Data Storage: Experience with relational databases (schema design, query optimization, migrations) and familiarity with NoSQL stores.

AI Adoption Across the SDLC :

This is not optional we expect SSE to model strong AI-augmented engineering practice:

• Uses AI coding assistants (e.g., Claude Code, Copilot) fluently for code generation, refactoring, and debugging not just autocomplete.
• Writes and iterates on prompts to produce high-quality, review-ready code and tests.
• Applies AI in design: uses LLMs to explore architectural tradeoffs, draft tech specs, generate ADRs, and sanity-check approaches.
• Integrates AI into testing: generates comprehensive test suites, edge-case matrices, and fuzz inputs.
• Uses AI for operations: log analysis, alert triage, root-cause summarization, runbook generation.
• Understands the limits of AI output reviews critically, catches hallucinations, and does not ship AI-generated code without verification.

Adaptability Polyglot Engineering :

• Python : Comfortable reading, writing, and shipping Python particularly for scripting, data pipelines, or ML-adjacent tooling. No need to be an expert, but must be willing to own Python services without friction.
• Polyglot mindset : Picks up new languages and frameworks as the job demands. Evaluates the right tool for the problem rather than defaulting to comfort.
• Infrastructure awareness : Familiar with cloud-native deployment (AWS/GCP/Azure), containerization (Docker/Kubernetes), and CI/CD pipelines.

Engineering Excellence :

• Ownership : Takes end-to-end accountability for features from requirements to rollout to monitoring. Does not need a manager to define done.
• Technical leadership : Drives design reviews, writes clear tech specs, mentors IC2/IC3 engineers, and raises the quality bar for the team.
• Collaboration : Works closely with product, data, and partner teams to understand integration requirements and translate them into robust technical solutions.
• Reliability focus : Thinks about failure modes first. Instruments everything. On-call capable and takes SLAs seriously.
• Communication : Can explain complex integration problems to non-technical stakeholders without losing accuracy.

Nice to Have :

• Experience with CRM/MarTech integrations (Salesforce, HubSpot, Marketo, etc.) or B2B data platforms.
• Familiarity with OAuth, SAML, or enterprise authentication patterns.
• Contributions to open-source projects or public technical writing.
• Experience in a team that ships ML-powered features or works alongside a data science team.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.