- Design and build integration services and APIs in Go, applying appropriate integration and design patterns including message routing, transformation, idempotency, retry/backoff, circuit breaker, saga/compensation, and outbox.

- Build event-driven flows using SQS, SNS, and Lambda, including ordering, deduplication, dead-letter handling, and replay strategy.

- Containerize services and deploy to EKS/Kubernetes; own Helm charts, resource sizing, health/readiness probes, autoscaling, and rollout strategy.

- Model and optimize data access against RDS, including schema design, indexing, connection pooling, transaction boundaries, and migrations.

- Translate integration requirements into interface contracts and sequence flows; document API and event schemas and drive versioning discipline.

- Build observability from day one through structured logging, metrics, distributed tracing, and alerting on integration SLAs.

- Use AI-assisted development tooling such as Claude Code, GitHub Copilot, and Cursor to accelerate delivery while ensuring AI-generated code meets the required quality and security standards.

- Contribute to CI/CD pipelines, automated testing including unit, contract, and integration testing, and non-functional validation including load, failover, and resiliency.

- Provide code review, mentoring, and technical guidance to mid-level developers; raise design risks early to the Tech Lead.

Must-Have Qualifications :

Go Development :

- Go hands-on experience is non-negotiable.

- 3+ years of experience writing production Go.

- Strong understanding of goroutines, channels, context propagation, error handling, and interface-driven design.

- Experience with Go web/API frameworks and gRPC or REST service development.

- Ability to profile and tune Go services for memory, concurrency, and latency.

Enterprise Integration :

- Working knowledge of enterprise integration patterns (Hohpe/Woolf) and their trade-offs, including sync vs. async, orchestration vs. choreography, guaranteed delivery, exactly-once vs. at-least-once, and idempotent consumers.

- Strong understanding of canonical data models for integration, including designing common schema layers, mapping source and target payloads, and determining when canonical models are appropriate versus point-to-point or per-domain contracts.

- Basic knowledge of one or more iPaaS platforms such as MuleSoft, Boomi, Workato, Azure Logic Apps, Informatica, TIBCO, webMethods, or similar, including connector development, mapping/transformation, and orchestration.

- Practical experience with creational, structural, and behavioral design patterns, clean architecture, SOLID, and domain boundaries.

- Experience with API contracts, schema evolution, and backward compatibility.

Cloud & Platform - AWS :

- Hands-on experience with EKS and Kubernetes, including deployments, services, ingress, config/secrets, HPA, and troubleshooting live workloads.

- Strong containerization skills with Docker, including multi-stage builds, image hardening, and small runtime images.

- Knowledge of SQS, SNS, and Lambda in event-driven architectures.

- Understanding of RDS (PostgreSQL or MySQL), including performance tuning.

- Knowledge of IAM, VPC/networking basics, Secrets Manager/Parameter Store, and CloudWatch.

AI in the Development Lifecycle :

- Demonstrable experience using AI coding assistants in real delivery, including the ability to explain what they accelerated, where the tooling failed, and how output was validated.

- Understanding of prompt/context practices for codebases and guardrails including security review, licensing, and hallucination checks.

Engineering Practice :

- Git-based workflow, trunk/branching discipline, and CI/CD using GitHub Actions, GitLab CI, Jenkins, or similar.

- Test automation habit covering unit, contract, and integration testing as part of the definition of done.

- Clear written and verbal communication with distributed teams and client stakeholders.