Custom Software Engineer

Accenture Federal Services • Herndon, VA

20h

About The Position

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! In this role, you will contribute to the design and development of robust, scalable, and secure backend systems and event-driven APIs using FastAPI. You will participate in code and technical design reviews to ensure high standards for quality, performance, and security. Collaboration with data scientists and ML engineers will be key to integrate, containerize, and deploy AI/ML models (e.g., NLP, recommendation engines, generative AI) into production environments. The position also involves engineering containerized applications for deployment on cloud platforms using Kubernetes and designing for scale using asynchronous processing and task queues (such as Celery, RabbitMQ, Kafka) to handle long running or unreliable tasks independently from the main API.

Requirements

• 4 to 7+ years of professional experience in one or more of the following areas: Python, with knowledge of the libraries and frameworks that make up the Python ecosystem.
• Designing and implementing RESTful APIs using tools like FastAPI.
• Asynchronous task processing tools like Celery and RabbitMQ.
• Strong working knowledge of Docker and Kubernetes for building and deploying scalable, cloud-native applications.
• Familiarity with distributed data orchestration and processing pipelines, using tools like Spark and Airflow.
• Relational databases like PostgreSQL.
• CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and/or deploying applications within the Linux ecosystem.
• Optimizing resources across cloud deployments for cost and performance benefit.
• Active TS/SCI with Poly clearance is required

Responsibilities

• Contribute to the design and development of robust, scalable, and secure backend systems and event-driven APIs using FastAPI.
• Participate in code and technical design reviews to ensure high standards for quality, performance, and security are met.
• Collaborate with data scientists and ML engineers to integrate, containerize, and deploy AI/ML models (e.g., NLP, recommendation engines, generative AI) into production environments.
• Engineer containerized applications for deployment on cloud platforms using Kubernetes.
• Design for scale using asynchronous processing and task queues (such as Celery, RabbitMQ, Kafka) to handle long running or unreliable tasks independently from the main API.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed