Software Engineer at Weekday AI

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Mar, 26

Salary

0.0

Posted On

06 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Celery, Temporal, Distributed Systems, Asynchronous Programming, Task Queues, Data Ingestion, ETL Pipelines, APIs, Message Brokers, Caching, Microservices, Debugging, Problem Solving, System Design, Data Lifecycle, Workflow Execution

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min Experience: 7 years Location: USA, United States JobType: full-time As a Software Engineer, you will be responsible for architecting and implementing high-performance backend systems that power large-scale data ingestion and processing workflows. You will work with asynchronous task orchestration engines, scalable data pipelines, and robust APIs. This role requires strong technical ownership, the ability to work independently, and a passion for building systems that operate seamlessly at scale. Your work will focus heavily on distributed task execution frameworks such as Celery and Temporal, creating fault-tolerant workflows, and ensuring consistent data delivery. You will design and optimize ingestion pipelines that handle multiple data formats, streaming inputs, and external integrations. This role also involves enhancing reliability, improving system performance, and introducing automation wherever possible. In addition to technical responsibilities, you will collaborate with product managers, data engineers, and platform teams to translate business needs into efficient and scalable engineering solutions. This role demands strong problem-solving skills, an analytical mindset, and the ability to think deeply about system design, data lifecycle, and workflow execution. Key Responsibilities1. Backend & Workflow Engineering Design and develop scalable backend services in Python. Build and maintain asynchronous task workflows using Celery and Temporal. Optimize queues, workers, schedules, and distributed job execution. Ensure fault tolerance, retry logic, and workflow resilience. 2. Data Ingestion & Pipeline Development Create robust data ingestion pipelines for large, diverse data sources. Implement parsing, transformation, validation, and loading workflows. Work with APIs, real-time streams, batch ingestion, and event-driven data flows. Improve throughput, latency, and ingestion accuracy. 3. Architecture & System Performance Contribute to architectural decisions around workflow orchestration, data modeling, and microservices. Improve system reliability, scalability, and observability. Implement logging, monitoring, alerting, and performance tuning. Ensure data security, privacy, and compliance across all pipelines. 4. Collaboration & Engineering Excellence Work closely with product, platform, data, and DevOps teams to align requirements and implementation. Write clean, maintainable, well-tested code following industry best practices. Conduct code reviews and mentor junior developers when needed. Document systems, workflows, and architecture decisions. What Makes You a Great Fit 7+ years of strong software engineering experience. Expert-level knowledge of Python and its backend frameworks. Hands-on experience with Celery, Temporal, or similar workflow orchestration systems. Strong understanding of distributed systems, asynchronous programming, and task queues. Proven experience building data ingestion or ETL pipelines at scale. Familiarity with APIs, message brokers, caching, and microservices patterns. Strong debugging and problem-solving ability, especially in production environments. Ability to write clean, efficient, and well-structured code. Excellent communication skills and comfort working with cross-functional teams. Strong ownership mindset with the ability to operate independently and proactively.

Responsibilities

The Software Engineer will design and develop scalable backend services and create robust data ingestion pipelines. They will also contribute to architectural decisions and collaborate with cross-functional teams to implement efficient engineering solutions.