AI Engineer

Title: Software Engineer (AI Engineer)
Contract Length: 24-36 months (2-3 years)

Location: Glendale CA 91201 United States

Work Location: Hybrid (4 days onsite in Glendale)

Education: Bachelors degree in a related field

Must have background and tools:
- Building app and deploying it to the cloud (ideally AWS) evidence of a database involved have knowledge of data bases UI level web based applications application stack in Python/Java/Node anything works there
- Need to know how to deploy app in a cloud and each layer of the app and the responsibilities of each. basic knowledge of people building enterprise platforms
- Need someone who can evaluate the outputs of AI and if they are good outputs not testing on knowing language more basic principles on cloud/web/database
- Experience with large files and databases

Soft skills:
- Excellent communication articulate
- Ability to speak with stakeholders have a product mindset when needed
- Someone who is adaptable able to pivot very quickly! cant be tied down to an idea

Tools:
- Can have any tool for AI they use Claude/Cursor right now but they are not locked into one AI tool theyre exploring
- Java Python or (any of these)
- AWS preferred open to other clouds as well

Day to Day Operations:
- Running 1 day sprints get together every morning for 30 min define goals then break into small teams of 1 - 2 product/engineer and get their work done for the day
- Need someone who can fit in this model of operating
- Run in start-up mode within an enterprise company right now
- Open to either background large enterprise or startup

Job Description:

Position Overview

• We are seeking a Software Engineer (Contract) to support the development of intelligent scalable systems within the Studio Digital Supply Chain.
• This role is focused on hands-on implementation of media workflows that blend deterministic orchestration with AI/ML-driven agentic behaviors.
• You will contribute to the design and delivery of cloud-native event-driven services that enable dynamic decision-making automation and human-in-the-loop processes.
• Ideal candidates have strong experience with distributed systems and cloud platforms and are comfortable implementing systems that integrate machine learning large language models or decision engines into real-world pipelines.

Key Responsibilities

AI-Augmented Workflow Development:

• Build features that support agentic behavior using AI/ML tools and APIs
• Integrate tools such as large language models (LLMs) decision engines and semantic search.

Workflow Orchestration & Automation:

• Implement deterministic workflows using state machines or rules engines
• Build hybrid models that support both structured and adaptive logic

Architecture & Scalability:

• Develop modular components within distributed systems
• Focus on reliability observability and performance at scale
• Contribute to platform infrastructure supporting media and content workflows

Event-Driven Development:

• Build services using Kafka EventBridge or SNS/SQS for asynchronous communication
• Ensure systems are resilient loosely coupled and scalable

API & Microservices Engineering:

• Deliver clean well-tested APIs and services in Java Python or
• Follow cloud-native design principles with containerization and CI/CD pipelines
• Maintain clear service boundaries and operational consistency

Cross-Functional Collaboration:

• Work closely with product engineering and ML teams to implement solutions
• Translate defined requirements into production-ready code
• Participate in sprint planning standups and delivery checkpoints

Basic Qualifications

• Experience integrating AI/ML tools LLMs or decision engines into applications
• Strong communication skills with an emphasis on high-quality maintainable code
• Experience integrating AI/ML tools large language models (LLMs) or decision engines into applications
• Bachelors or masters degree in a Computer Science Software Engineering or a related field.
• 3-5 years of experience building distributed cloud-native backend systems
• Strong understanding of AWS services and event-driven architecture
• Proficiency in Java or
• Familiarity with Docker Kubernetes and modern CI/CD workflows
• Strong communication skills and a focus on delivering high-quality maintainable code

Preferred Qualifications

• Java/Javascript Node Python
• Experience in Media or Entertainment especially studio or post-production environments
• Background in multi-tenant platforms or shared infrastructure
• Hands-on experience with machine learning systems pipelines or model integration in production environments
• Familiarity with Agile and DevOps methodologies

Required Education

• Bachelors degree in a related field