Agentic AI Engineer

Oscar Technology; Atlanta (GA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive pay

Hybrid work options

Health benefits

Job summary

Oscar Technology seeks an AI Engineer to lead the development of high-performance backend systems, data pipelines, and compute orchestration layers. You will connect physics-based simulation engines with AI agent workflows for global enterprise clients.

Responsibilities include designing scalable Python microservices, building robust data pipelines (RAG, Delta Lake), and integrating agentic compute orchestration with secure cloud environments.

Qualifications

• This role requires 6 years of production software engineering experience building scalable backend microservices and high-throughput distributed systems.
• Strong Python expertise with modern web frameworks and databases; familiarity with FastAPI, gRPC, PostgreSQL, and Redis.
• Experience containerizing and orchestrating services with Docker/Kubernetes and using IaC tools like Terraform on major cloud platforms.
• Hands-on experience with asynchronous task processing (Celery, RabbitMQ) and large-scale data pipelines.
• Educational background in a quantitative field as listed above.

Responsibilities

• Lead design and development of high-concurrency Python backend microservices powering simulations and active learning loops.
• Build scalable data pipelines and integration layers (RAG, Delta Lake) for a unified semantic data platform.
• Collaborate with AI/ML teams to integrate agentic workflows and model-serving in secure cloud environments.
• Enhance operational excellence through multi-tenancy, security, auditability, and CI/CD automation.

Skills

Python

FastAPI

gRPC

PostgreSQL

Redis

Docker

Kubernetes

Terraform

AWS

Azure

GCP

Celery

RabbitMQ

Distributed systems

APIs

CUDA

Education

B.S. or M.S. in Computer Science, Software Engineering, Applied Mathematics, or related field

Tools

Docker

Kubernetes

Terraform

AWS

Azure

GCP

Job description

Role

We are seeking an AI Engineer to lead the development of our high-performance backend systems, data pipelines, and compute orchestration layers. You will build the core platform infrastructure that connects physics-based simulation engines and AI agent workflows with global enterprise clients.

Key Responsibilities

System Architecture: Design, build, and maintain high-concurrency backend microservices in Python that power complex physical simulations and active learning loops.

Data Pipelines & Integration: Build scalable ingestion and processing pipelines (RAG, Delta Lake) to unify fragmented enterprise data and physical schemas into a high-performance semantic layer.

Agentic Compute Orchestration: Partner with AI/ML research teams to integrate agentic workflows, sandboxed execution systems, and model-serving infrastructure into secure, enterprise-grade cloud environments.

Operational Excellence: Harden core system capabilities around multi-tenancy, security, auditability, CI/CD automation, and low-latency API performance.

Qualifications

Experience: 6 years of production software engineering experience building scalable backend microservices, high-throughput distributed systems, and API architectures.

Core Tech Stack: Advanced proficiency in Python, alongside modern web frameworks (FastAPI, gRPC) and relational/NoSQL databases (PostgreSQL, Redis).

Infrastructure & Cloud: Strong experience with containerization, orchestration, and IaC tools including Docker, Kubernetes, and Terraform on AWS, Azure, or Google Cloud Platform.

Data & Systems: Hands-on experience with asynchronous task processing (Celery, RabbitMQ), large-scale data pipelines, and high-performance system design.

Education: B.S. or M.S. in Computer Science, Software Engineering, Applied Mathematics, or a related quantitative field.

Preferred / Bonus Qualifications

Experience or background in CAD engines, CAE/CFD software, computational physics, or digital twin simulation platforms.

Exposure to physics-informed machine learning models, active learning loops, or autonomous LLM multi-agent orchestration.

Knowledge of C/C++ low-level optimization, CUDA, or parallel compute systems.

Benefits

• This role offers competitve pay, hybrid work options, and comprehensive health benefits.