Here is the complete refactored package structure. Each module follows the single responsibility principle, uses proper relative imports, and avoids circular dependencies via `TYPE_CHECKING`.

### `queue/__init__.py`
```python
"""
Job Queue Package
A modular job processing system with priority ordering and retry capabilities.
"""
from .core import Job, JobQueue
from .retry import process_with_retry

__all__ = ["Job", "JobQueue", "process_with_retry"]
```

### `queue/core.py`
```python
"""
Core domain model and high-level queue interface.
"""
from __future__ import annotations
import time
import uuid
from dataclasses import dataclass, field
from typing import Callable, Any, Optional
from .priority import PriorityQueue


@dataclass
class Job:
    """Represents a unit of work to be processed."""
    id: str = field(default_factory=lambda: str(uuid.uuid4()))
    func: Callable[..., Any] = None
    args: tuple = ()
    kwargs: dict = field(default_factory=dict)
    priority: int = 0  # Lower number = higher priority
    max_retries: int = 3
    retry_count: int = 0
    created_at: float = field(default_factory=time.time)


class JobQueue:
    """
    High-level job queue interface.
    Delegates ordering to PriorityQueue and exposes basic operations.
    """
    def __init__(self) -> None:
        self._queue = PriorityQueue()

    def enqueue(self, job: Job) -> None:
        """Add a job to the queue."""
        self._queue.push(job)

    def dequeue(self) -> Optional[Job]:
        """Remove and return the highest priority job, or None if empty."""
        return self._queue.pop()

    def __len__(self) -> int:
        return len(self._queue)

    def __bool__(self) -> bool:
        return bool(self._queue)
```

### `queue/priority.py`
```python
"""
Priority queue implementation using a binary heap.
"""
from __future__ import annotations
import heapq
from typing import Optional, TYPE_CHECKING

if TYPE_CHECKING:
    from .core import Job


class PriorityQueue:
    """Thread-unsafe priority queue for Job objects."""
    def __init__(self) -> None:
        self._heap: list[tuple[int, int, Job]] = []
        self._counter: int = 0  # Tie-breaker for FIFO ordering of same priorities

    def push(self, job: Job) -> None:
        """Add a job to the priority queue."""
        heapq.heappush(self._heap, (job.priority, self._counter, job))
        self._counter += 1

    def pop(self) -> Optional[Job]:
        """Remove and return the highest priority job."""
        if self._heap:
            _, _, job = heapq.heappop(self._heap)
            return job
        return None

    def __len__(self) -> int:
        return len(self._heap)

    def __bool__(self) -> bool:
        return bool(self._heap)
```

### `queue/retry.py`
```python
"""
Retry logic with exponential backoff and jitter.
"""
import random
import time
from typing import Any
from .core import Job


def process_with_retry(
    job: Job,
    base_delay: float = 1.0,
    max_delay: float = 60.0,
) -> Any:
    """
    Execute a job with exponential backoff on failure.

    Args:
        job: The Job instance to execute.
        base_delay: Initial delay in seconds between retries.
        max_delay: Maximum delay in seconds between retries.

    Returns:
        The return value of the job's callable.

    Raises:
        Exception: The last exception raised if all retries are exhausted.
    """
    last_exception: Exception | None = None

    for attempt in range(job.max_retries + 1):
        try:
            return job.func(*job.args, **job.kwargs)
        except Exception as e:
            last_exception = e
            job.retry_count += 1

            if job.retry_count > job.max_retries:
                break

            # Exponential backoff with 10% random jitter to prevent thundering herd
            delay = min(base_delay * (2 ** (job.retry_count - 1)), max_delay)
            jitter = random.uniform(0, delay * 0.1)
            time.sleep(delay + jitter)

    raise last_exception
```

### Key Design Decisions:
1. **Circular Import Prevention**: `priority.py` uses `TYPE_CHECKING` to import `Job` only for type hints. This allows `core.py` to import `PriorityQueue` at runtime without triggering a circular dependency.
2. **Single Responsibility**: 
   - `core.py` handles the domain model (`Job`) and the public facade (`JobQueue`)
   - `priority.py` encapsulates the heap-based ordering algorithm
   - `retry.py` isolates fault-tolerance logic (exponential backoff + jitter)
   - `__init__.py` acts as the clean public API surface
3. **Modern Python Practices**: Uses `from __future__ import annotations` for forward references, dataclasses for immutable-by-default job definitions, and explicit type hints throughout.
4. **Thread-Safety Note**: The priority queue is intentionally kept thread-unsafe for performance. If concurrency is needed, wrap `push`/`pop` with a `threading.Lock` or use `queue.PriorityQueue` from the standard library.