We are
At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud \& DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets.
Roles and Responsibilities:
Have demonstrable experience leading and building scalable microservices and event-driven applications
Can solve complex technical challenges from design through to production
Address tech debt with a pragmatic, commercially focused approach
Translate requirements into solid engineering deliverables
Deliver reusable solutions used across teams and products
Collaborate across teams and align technical decisions with business goals
Expertise in observability and reliability practices, leveraging tools such as OpenTelemetry, Prometheus, Grafana and CloudWatch
A solid understanding of security best practices, including Vault, AWS Secrets Manager and certificate management
Experience with testing methodologies (TDD, BDD) and automation frameworks
Ability to design and implement data-intensive applications and scalable architectures (API, microservices, event-driven, serverless)
Knowledge of deployment strategies and SRE principles
Interest or experience in AI/ML technologies and emerging tools
Skills:
Programming: Java, TypeScript and JavaScript (Node.js) ,Springboot building scalable, high-performance services.
Frameworks \& Platforms: . Java,React (TypeScript), Springboot EE for RESTful APIs and enterprise applications.
Architecture: Microservices, Domain-Driven Design (DDD), event-driven systems using RabbitMQ and/or Apache Kafka.
Databases: SQL Server, PostgreSQL, and/or other relational/NoSQL databases – e.g., PostgreSQL and DynamoDB
Cloud (AWS): EC2, Lambda, ECS/Fargate, RDS, DynamoDB, CloudFormation, CDK, CodePipeline, CodeBuild, CloudWatch.
CI/CD: TeamCity, Octopus Deploy, GitHub \& GitHub Actions.
Containers: Kubernetes and Docker.
Infrastructure as Code: Terraform, CloudFormation, Ansible.
Quality Engineering: Strong advocate for automated testing and quality-driven delivery.
AI \& Chatbot Integration: Exposure to building AI-driven support tools, such as integrating with LLMs/ChatGPT for developer support