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Remote Unity Developer Jobs in Los Angeles, CA (NOW HIRING)

NEOGOV

Senior Software Engineer

El Segundo, CA · On-site +1

$184K/yr

Remote Job Type: Full-Time Remote Employment: Remote Optional Job Number: 00943 Department: Development Opening Date: 08/20/2026 About Job Title: Sr. Software Engineer Duties: The Sr. Software ...

Fuser

Creative Solutions Manager

Los Angeles, CA · Remote

$4.0K - $6.0K/mo

... Unity etc.) * Familiarity with APIs, AI models, or automation (Zapier, n8n, etc.) * Strong ... Hybrid, flexible, async-friendly-- based in LA with remote option for exceptional candidates

Civic Canvas

Software Engineer

Los Angeles, CA · Remote

$105K - $130K/yr

This is a remote position. We are seeking a talented Software Engineer to join our engineering team and help design, build, and support modern, scalable software solutions. This role is ideal for a ...

PTP

Software Engineer - REMOTE

CA · On-site +1

We are looking for a Senior Software Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude and ...

JF Retail Services

Software Engineer II

El Segundo, CA · On-site +1

$120K - $140K/yr

This role is remote-friendly, with headquarters based in El Segundo, CA Compensation & Total Rewards: At Fabletics, we believe work and life should fit together!We continue to build a culture of ...

NxT Level

Senior Tools Engineer

Los Angeles, CA · On-site +1

$112K - $154K/yr

Our client is looking for a Tools Programmer to join their fully remote team to build next generation MMOs and Multiplayer Games. They currently need a programmer passionate about terrain and ...

G4 Furniture USA LLC

Furniture Engineer

Brea, CA · On-site +1

$72K - $80K/yr

Optional WFH/Remote Essential Duties * Draft and review product schematics based on project ... Provides critical guidance to the engineering department/function using technical knowledge and ...

PVM Inc

Forward Deployed Engineer

Los Angeles, CA · Remote

$107K - $146K/yr

Remote: Must reside in or near Los Angeles, CA - Will need to go onsite occassionally Reports to: Echo Direct reports: None. Delta's provide performance feedback on other engineers and participate in ...

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All JobsUnity Developer JobsRemote Unity Developer JobsRemote Unity Developer Jobs in Los Angeles, CA

Remote Unity Developer information

See Los Angeles, CA salary details

$35K

$116.9K

$194K

How much do remote unity developer jobs pay per year?

As of Aug 24, 2026, the average yearly pay for remote unity developer in Los Angeles, CA is $116,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $133,600.00 per year, depending on experience, location, and employer.

What is a remote Unity developer?

A Remote Unity Developer is a software engineer who specializes in developing applications, primarily games, using the Unity engine while working from a remote location. They are responsible for coding, debugging, and optimizing game mechanics, graphics, and performance. They collaborate with designers, artists, and other developers using online communication tools. This role may also involve integrating third-party APIs, testing, and deploying applications to various platforms. Remote Unity Developers must be proficient in Unity, C#, and game development principles while managing their workflow independently.

What does a remote Unity developer do?

Remote Unity Developers spend their days designing, coding, and refining interactive applications or games within the Unity engine, frequently collaborating with artists, designers, and other programmers through virtual communication tools. They are often responsible for implementing gameplay features, optimizing performance, debugging issues, and integrating assets such as 3D models, audio, and animations. Additionally, participation in regular stand-ups or sprint reviews is common, helping keep projects on track and aligning with the broader team's goals. The remote nature of the role means strong self-management and proactive collaboration are especially important to ensure deadlines are met and quality standards are upheld.

What skills and qualifications are needed to be a remote Unity developer?

A Remote Unity Developer should have solid experience in C# programming, a thorough understanding of the Unity game engine, and a relevant degree or equivalent professional experience in software development or game design. Proficiency with version control systems like Git, familiarity with agile development methodologies, and optionally, Unity Certified Developer credentials are commonly expected. Excellent communication, problem-solving abilities, and strong self-motivation are crucial for working effectively in distributed teams. These competencies enable developers to create high-quality interactive experiences while collaborating seamlessly across different locations and time zones.

What are the most commonly searched types of Unity Developer jobs in Los Angeles, CA?

The most popular types of Unity Developer jobs in Los Angeles, CA are:

What are popular job titles related to Remote Unity Developer jobs in Los Angeles, CA?

For Remote Unity Developer jobs in Los Angeles, CA, the most frequently searched job titles are:

What job categories do people searching Remote Unity Developer jobs in Los Angeles, CA look for?

The top searched job categories for Remote Unity Developer jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Remote Unity Developer jobs?

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Remote Unity Developer jobs near you
Infographic showing various Remote Unity Developer job openings in Los Angeles, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $116,878 per year, or $56.2 per hour.

Software Engineer - AI Systems (Go)

Irvine, CA • On-site, Remote

Stanbridge University
Colleges, Universities, and Professional Schools • 201 - 500 employees
Learn more about Stanbridge Universityexternal

Full-time

Posted 4 days ago

Job description

Stanbridge University is seeking Software Engineers - AI Systems (Go) to design, build, and operate production AI systems that perform complex, multi-stage work reliably and at scale.
This is a hands-on engineering role focused on a challenging class of problems: long-running AI workflows that call models, tools, and external APIs; maintain state across extended executions; produce structured content and generated media; interact with human reviewers; recover from partial failures; and consistently deliver accurate results to users.
The core engineering challenges extend well beyond prompt development. These systems must account for provider failures and rate limits, interrupted workflows, changing state, non-deterministic model behavior, incorrect or unsupported outputs, variable latency and cost, and deployments occurring while work is in progress.
The successful candidate will combine strong software and distributed-systems engineering judgment with practical experience building and operating LLM-backed applications, AI agents, or agent-based systems in production.
You will join at a stage where significant architecture remains to be designed and built. Engineers in this role will have substantial ownership over the patterns, services, infrastructure, and engineering standards that shape the University's AI systems.
Remote Work Eligibility
This position is eligible for remote work for candidates residing in states where Stanbridge University is currently authorized to employ remote employees. Eligible states currently include: Arizona, Colorado, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maryland, Michigan, Minnesota, Nevada, New Jersey, North Carolina, North Dakota, Ohio, Tennessee, Texas, and Wisconsin.
Candidates must reside in an eligible state at the time of employment. Remote-work eligibility is subject to University employment requirements and may change based on applicable state requirements.
Engineering Environment
The engineering problems addressed by this team include:
  • Durable workflow orchestration: Long-running, multi-stage pipelines using persistent state, job queues, checkpoints, resumability, idempotent execution, and recovery from interrupted or orphaned work.
  • Multi-provider model infrastructure: Routing across commercial model providers with model registries, token and cost controls, rate-limit handling, retries, circuit breakers, health monitoring, and provider failover.
  • Agent and tool orchestration: Systems in which AI agents interact with tools, APIs, data sources, application services, and deterministic business logic to complete multi-step work.
  • Prompt engineering infrastructure: Treating prompts as version-controlled production artifacts with review, testing, regression protection, and measurable behavior.
  • Testing non-deterministic systems: Recorded and replayable provider interactions, deterministic fixtures, evaluation harnesses, baselines, and regression testing for AI behavior.
  • Correctness and quality controls: Structured-output validation, automated evaluation, domain-specific requirements, evidence checking, and safeguards against confident but incorrect model output.
  • Human-in-the-loop workflows: Review and approval stages within automated processes, including systems capable of safely responding when users modify state or inputs during execution.
  • Generated media pipelines: Systems capable of producing and managing documents, audio, imagery, video, and other generated assets.
  • Production service architecture: Go-based APIs and backend services, relational data stores, job infrastructure, observability, and integrations supporting user-facing applications.
  • Secure ingestion: Processing user-supplied and potentially untrusted documents while maintaining appropriate security and authorization boundaries.
Two Engineering Emphases
Engineers will meet the same overall technical bar but may bring deeper expertise in one of two areas:
Platform and Pipeline
Focused on distributed systems, workflow orchestration, durable state, job queues, recovery, provider infrastructure, latency, throughput, scalability, reliability, and cost optimization.
This emphasis is particularly well suited for experienced systems engineers who view AI models as powerful components that introduce a new set of distributed-systems and reliability challenges.
Agents and Quality
Focused on agent and tool architecture, prompt systems, context management, evaluation frameworks, regression testing, judge models, evidence validation, and end-to-end output quality.
This emphasis is particularly well suited for engineers who approach AI behavior through experimentation, measurement, testing, and systematic improvement.
Candidates may indicate an area of preference; however, specialization in one area is not required.
Essential Functions
  • Design, develop, test, deploy, and operate production-quality software and backend services, primarily using Go (Golang).
  • Architect and build AI agents and agent-based systems capable of using tools, interacting with APIs, maintaining state and context, and executing complex multi-step workflows.
  • Design durable workflows that can checkpoint, resume, retry, recover, and safely continue execution following partial failures or system interruptions.
  • Determine how models, agents, tools, APIs, data sources, services, and deterministic application logic should divide responsibilities within an AI system, including recognizing when an AI model is not the appropriate solution.
  • Design integrations across multiple AI model providers, including routing, failover, rate-limit management, health monitoring, and degradation strategies.
  • Build safeguards including structured-output validation, error handling, retries, quality gates, evidence validation, and automated recovery mechanisms.
  • Develop testing strategies for non-deterministic AI behavior using techniques such as deterministic fixtures, recorded and replayed interactions, regression suites, evaluation harnesses, and quality baselines.
  • Develop observability capabilities including tracing, metrics, logging, evaluation data, and replayable execution histories to support production debugging and performance analysis.
  • Design human-in-the-loop workflows incorporating review, approval, intervention, and modification of workflow state.
  • Build and maintain APIs, backend services, relational data models, job-processing infrastructure, and supporting application components.
  • Develop secure methods for ingesting and processing user-supplied documents and other external content.
  • Optimize systems for reliability, latency, throughput, scalability, output quality, and cost per execution.
  • Build reusable engineering patterns and shared components that simplify the addition of new agents, model providers, tools, workflows, and output types.
  • Own technical problems from initial investigation and architecture through implementation, deployment, monitoring, troubleshooting, and ongoing production operation.
  • Collaborate directly with product stakeholders and domain experts to translate qualitative requirements into measurable system behavior and technical solutions.
  • Contribute to architectural decisions and engineering standards for AI-powered applications across the University.
Qualifications
Required
  • Substantial professional experience developing and operating production software, with strong experience in Go (Golang) or demonstrated depth in another backend language with the ability to become productive in Go quickly.
  • Hands-on experience shipping an LLM-backed application, AI agent, or agent-based system into production and supporting it after deployment.
  • Strong understanding of AI application architecture, including how models, agents, tools, APIs, data sources, services, and application logic interact.
  • Demonstrated distributed-systems engineering knowledge, including concurrency, asynchronous processing, queues, idempotency, retries, partial failure, state management, and recovery.
  • Experience designing systems that remain reliable when individual services, providers, or workflow stages fail.
  • Demonstrated testing discipline for systems involving non-deterministic behavior.
  • Strong experience designing and consuming HTTP APIs.
  • Experience with relational databases, SQL, and persistent application state.
  • Experience building, deploying, monitoring, and troubleshooting backend services in production environments.
  • Understanding of software architecture, testing, debugging, observability, and production engineering practices.
  • Ability to independently own ambiguous technical problems from investigation through production implementation.
  • Strong analytical judgment and the ability to balance reliability, quality, performance, complexity, and cost.

Preferred Qualifications
  • Experience with AI agent frameworks, orchestration patterns, or custom agent architectures, including an understanding of when a framework may not be appropriate.
  • Experience with retrieval-augmented generation (RAG), embeddings, vector databases, semantic search, or knowledge-retrieval architectures.
  • Experience developing evaluation and observability systems for LLM applications, including tracing, regression suites, quality dashboards, or automated evaluation.
  • Experience with judge models, structured-output validation, evidence checking, or other AI quality-control mechanisms.
  • Experience designing human-in-the-loop workflows involving review, approval, intervention, or modification of active workflow state.
  • Experience with document processing, headless-browser rendering, text-to-speech, image generation, video generation, or other media pipelines.
  • Experience with event-driven architectures, durable job queues, and asynchronous processing at scale.
  • Experience with containers, cloud infrastructure, CI/CD, and production deployment environments.
  • Understanding of prompt injection, authorization boundaries, data isolation, and security considerations when untrusted content is processed by AI systems.
  • Experience developing systems in environments where the accuracy of generated output carries significant operational, regulatory, compliance, or safety implications.
What Success Looks Like
An exceptional engineer in this role will:
  • Build AI workflows that operate reliably in production without requiring routine human intervention.
  • Design systems that recover gracefully from model-provider failures, interrupted execution, deployments, rate limits, and other partial failures.
  • Make AI behavior increasingly measurable, reproducible, testable, and observable rather than relying on subjective evaluation.
  • Improve output quality while systematically reducing latency and cost per execution.
  • Create durable engineering patterns that make subsequent agents, providers, workflows, and output types easier and safer to introduce.
  • Identify when deterministic software should replace or constrain model-driven behavior.
  • Build systems whose failures can be diagnosed through instrumentation and replay rather than guesswork.
  • Establish architecture and engineering practices that become foundational components of the University's broader AI capabilities.
Compensation
Compensation is based on education, experience, and qualifications and internal equity
Conditions of Employment:
  • A job-related assessment may be required during the interview process.
  • Must be able to perform each essential duty satisfactorily and be physically present in the office (unless otherwise noted).
  • Employment Authorization: Applicants must be legally authorized to work in the United States. Stanbridge University does not provide employment-based immigration sponsorship or participate in employer-sponsored or employer-dependent work authorization programs.
  • Sponsorship: Sponsorship now or in the future could include having Stanbridge University sponsor, complete employer documentation, provide attestations or training plans, or otherwise participate in a work-authorization or employment-based immigration program in order for an individual to begin or continue employment. Stanbridge University does not provide any such sponsorship.
  • Employment verification will be conducted to validate work experience per accreditation standards.
  • Offers of employment are contingent upon the successful completion of a background check.
  • Official transcripts are required prior to hire. Degrees earned outside the United States must be evaluated by a recognized credential evaluation service to determine U.S. degree equivalency and applicable subject-area coursework.
  • Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
Work Environment
  • Standard professional and technology-focused work environment.
  • Duties are typically performed while sitting at a desk or computer workstation.
  • Position requires extensive interaction with computers, software development environments, cloud services, AI systems, and technical infrastructure.
  • Subject to collaboration with cross-functional teams, changing technical requirements, and demanding project timelines.
Physical Demands
  • Regularly sits for extended periods.
  • Physical ability to perform department-related dutie

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