While your message may appear to be read in a round robbin fashion, they are not actually consumed in a round robin. SQS works by making all messages available to any consumer (that has the appropriate IAM permissions) and hides the message as soon as one consumer fetches the message for a pre-configured amount of time that you can configure, effectively "locking" that message. The fact that all of your consumer seem to be operating in a round robin way is most likely coincidental.
As others have mentioned you could use SNS instead of SQS to fanout messages to multiple consumers at once, but that's not as simple a setup as it may sound. If your service B is load balanced, the HTTP endpoint subscriber will point to the Load Balancer's DNS name, and thus only one instance will get the message. Assuming your instances have a public IP, you could modify your app so that it self-registers as an HTTP subscriber to the topic when the application wakes up. The downsides here are that you're not only bypassing your Load Balancer, you're also losing the durability guarantees that come with SQS since an SNS topic will try to send the message X times, but will simply drop the message after that.
An alternative solution would be to change the message hiding timeout setting on the SQS queue to 0, that way the message is never locked and every consumer will be able to read it. That will also mean you'll need to modify your application to a) not process messages twice, as the same message will likely be read more than once by the time it has finished processing and b) handle failure gracefully when one of the instance deletes the message from the queue and other instances try to delete that message from the queue after that.
Alternatively, you might want to use some sort of service mesh, or service discovery mechanism so that instances can communicate between each other in a peer-to-peer fashion so that one instance can pull the message from the SQS queue and propagate it to the other instances of the service.
You could also use a distributed store like Redis or DynamoDB to persist the messages and their current status so that every instance can read them, but only one instance will ever insert a new row.
Ultimately there's a few solutions out there for this, but without understanding the use-case properly it's hard to make a hard recommendation.