AI Software Engineer | LLMs, RAG & Private AI - Interview Today - Start Tomorrow

Job Description

Job Description

Job details

• Company: MemeHouse, LA

• Location: Beverly Hills, CA In Person and Remote

• Employment type: Full-time, Part-Time, W-2 employee, or Contract

• Annual base salary: $130,000–$180,00

• Additional compensation: $5,000 performance-based signing incentive, earned through two initial-delivery milestones targeted for the first 90 days

About us

At MemeHouse LA, we build AI software that helps businesses turn their information into useful decisions and reliable workflows. Our focus is practical: secure AI deployments, connected business systems, and applications that deliver measurable value.

We are looking for an engineer who wants to build more than demonstrations. You will help create dependable AI capabilities, from model selection and data integration through deployment, evaluation, security, and ongoing improvement.

About the role

As an AI Software Engineer, you will design, build, and deploy AI-powered applications using large language models, retrieval-augmented generation, and modern software engineering practices. You will work across the application and infrastructure stack, helping translate business requirements into systems that users can trust.

This is a hands-on role with ownership of meaningful technical deliverables. You will collaborate with product and business stakeholders, explain technical trade-offs, and help establish repeatable practices as the team grows.

What you will do

• Build AI applications: Develop production-oriented LLM features, retrieval systems, workflow automations, and APIs that address defined business needs.

• Deploy private models: Evaluate and serve appropriately licensed open-weight models on private, dedicated, or customer-controlled infrastructure.

• Connect business data: Integrate approved documents, databases, CRMs, business applications, and other structured or unstructured data sources.

• Engineer reliable retrieval: Build ingestion, indexing, embedding, retrieval, and citation workflows with appropriate access controls.

• Evaluate quality: Create repeatable tests for response quality, groundedness, latency, cost, and failure modes; use results to guide improvements.

• Operate dependable systems: Implement deployment pipelines, observability, error handling, versioning, rollback procedures, and operational documentation.

• Protect sensitive information: Apply least-privilege access, secrets management, tenant separation where applicable, and safeguards against prompt injection and unintended data disclosure.

• Improve the engineering function: Participate in code reviews, document architectural decisions, share findings, and help mentor additional engineers as the team expands.

What we are looking for

• Software engineering ability: Strong Python skills and demonstrated experience building maintainable software, APIs, automated tests, and data integrations.

• Applied AI experience: Hands-on work with LLM applications, embeddings, RAG, model evaluation, or fine-tuning when appropriate.

• Relevant tooling: Experience with tools such as PyTorch, Hugging Face Transformers, vLLM, LangChain, or LlamaIndex. We value sound engineering judgment over familiarity with every listed tool.

• Backend and deployment fundamentals: Comfort with SQL, Git, Linux, Docker, API authentication, and CI/CD workflows.

• Data engineering knowledge: Experience processing business data and designing reliable ingestion or transformation pipelines.

• Security awareness: Ability to reason about data privacy, permissions, model limitations, and secure deployment.

• Ownership and communication: Ability to scope work, communicate blockers early, document decisions, and deliver usable results.

• Demonstrated capability: Relevant professional experience, substantial project work, or equivalent evidence of technical proficiency. A specific degree is not required.

Helpful additional experience

• GPU and inference optimization: CUDA, quantization, batching, GPU memory management, or inference benchmarking.

• Infrastructure: Kubernetes, infrastructure as code, private networking, or on-premises deployments.

• Business integrations: CRM, ERP, finance, document-management, or analytics platforms.

• Advanced evaluation: Permission-aware retrieval testing, adversarial testing, or production AI observability.

• Team contribution: Open-source work, technical writing, or mentoring other engineers.

Your first 90 days

• First 30 days: Understand the architecture, security requirements, and priority use case; establish the development environment and evaluation approach.

• Target by day 45: Deliver a working AI prototype connected to an approved data source, with reproducible setup instructions and initial evaluation results.

• Target by day 90: Deliver a production-ready version of the agreed feature in an approved staging or production environment, supported by automated tests, monitoring, and a deployment and rollback runbook.

Compensation and $5,000 signing incentive

The annual base salary range is $130,000–$180,000. The starting offer will reflect the responsibilities of the position, demonstrated skills, relevant experience, and internal pay equity; the $5,000 incentive is separate from base salary.

We offer a $5,000 gross performance-based signing incentive , structured as a new-hire milestone bonus rather than an upfront payment:

• Milestone one: $2,500. Earned upon completion of the agreed prototype, data integration, and initial evaluation deliverables, targeted for day 45.

• Milestone two: $2,500. Earned upon completion of the agreed production-readiness, testing, monitoring, and documentation deliverables, targeted for day 90.

Written milestone requirements and objective acceptance criteria will be provided before employment begins. Each installment is earned when its criteria are satisfied and will be paid on the next regular payday, or earlier if required by applicable law, less required tax withholdings.

The 45- and 90-day dates are delivery targets, not minimum-service or automatic-forfeiture dates. Once earned, an installment is not conditioned on continued employment through its payment date and does not have to be repaid if employment later ends.

Benefits

• Health coverage: Employer-sponsored health insurance, subject to plan eligibility and terms.

• Retirement benefits: 401(k) participation, subject to plan eligibility and terms.

• Time off: Unlimited paid time off under the company’s written policy, plus applicable paid sick leave and other legally protected leave.

Why join us?

You will have direct ownership of useful AI capabilities and the opportunity to shape how they are built and operated. We value clear thinking, candid communication, responsible handling of customer information, and engineering that holds up beyond the demo.

Equal opportunity and accommodations

MemeHouse LA is an equal opportunity employer. We consider qualified applicants without discrimination based on any characteristic protected by applicable federal, state, or local law and provide reasonable accommodations during the application process and employment.

How to apply

Submit your resume and, if available, a GitHub profile, portfolio, or short description of a relevant AI project to us. Please do not submit confidential information belonging to a current or former employer or client.