Job Title : Senior .NET/.NET Core Software Engineer - Microservices & AI (AWS)

Role summary :

Seeking a senior software engineer with strong expertise in .NET and .NET Core 8.0 to design, build, and operate scalable microservices on AWS. The role combines modern backend engineering, cloud-native architecture, proven design-patterns, and applied AI/ML integration to deliver reliable, performant services and intelligent features.

Key responsibilities :

- Design, implement, test, and maintain backend services using .NET and .NET Core 8.0.

- Architect and build cloud-native microservices (domain-driven design, bounded contexts, service contracts).

- Deploy and operate services on AWS (ECS/Fargate, EKS, Lambda, API Gateway, RDS/DynamoDB, S3, CloudWatch).

- Implement robust CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation, or CDK).

- Apply software design patterns and best practices (SOLID, CQRS, Event Sourcing, Repository, Factory, Dependency Injection).

- Design and manage inter-service communication (REST, gRPC, messaging with Kafka/SQS/EventBridge).

- Ensure observability: logging, metrics, tracing (OpenTelemetry, CloudWatch, Prometheus/Grafana).

- Integrate AI/ML capabilities into products (model inference, embeddings, vector search, prompt orchestration, or leveraging managed AI services).

- Optimize for performance, scalability, security, and cost-efficiency.

- Conduct code reviews, mentor team members, and contribute to architectural decisions.

- Collaborate with product, data science, DevOps, and QA teams.

Required qualifications :

- 5+ years professional experience building backend systems with C# and .NET (.NET Core experience required).

- Hands-on experience with .NET Core 8.0 (or demonstrated rapid mastery of latest .NET Core versions).

- Proven experience designing and implementing microservices architectures.

- Strong AWS experience: compute, networking, storage, databases, IAM, monitoring.

- Solid understanding and practical use of software design patterns and architecture principles.

- Familiarity with containerization (Docker) and orchestration (Kubernetes / ECS).

- Experience with CI/CD tools and IaC (GitHub Actions, Jenkins, GitLab CI, Terraform, CloudFormation, or CDK).

- Practical experience integrating AI/ML features or working with ML engineers (model deployment, inference, using managed AI services or SDKs).

- Strong testing discipline (unit, integration, contract tests).

- Excellent problem-solving, communication, and collaboration skills.

Interview Rounds :

- 3 Rounds (L1 - F2F, L2 - Virtual, Final - Virtual)

Work mode : WFO-5 days

Shift Timing : 1-10 PM shift (Drop cab facility is there)