AI Forward Deployed Engineer

About the role

Title: AI Forward Deployed Engineer

Full-Time | Mid Level | 3+ Years Experience | Individual Contributor

Location: Long Beach, California / onsite

Direct Hire

About the Role

We are looking for an AI Forward Deployed Engineer who combines strong software engineering fundamentals with hands-on experience deploying AI into real products, workflows, and business operations.

This is not an AI research or pure ML role. We are looking for an excellent software engineer who knows how to use AI and LLM technologies to solve real problems, accelerate development, and deliver measurable business impact.

You will own projects end to end — from identifying a business problem and designing the solution to building, deploying, monitoring, and improving production systems.

What You'll Do

Software Engineering

Design, build, and maintain scalable production software and APIs.

Write clean, maintainable, well-tested code.

Design and optimize relational and NoSQL databases.

Debug complex production issues and improve system performance.

Contribute to architecture decisions and evaluate technical tradeoffs.

Participate in code reviews and help maintain a high engineering standard.

AI & LLM Deployment

Identify opportunities where AI can create meaningful business or customer value.

Build and deploy LLM-powered features and workflows into production.

Integrate LLM APIs and AI frameworks into applications, internal tools, and business processes.

Develop AI capabilities such as search, summarization, recommendations, intelligent automation, and decision support.

Use AI coding tools such as GitHub Copilot, Cursor, and Claude Code to accelerate development.

Evaluate AI-generated output critically and apply engineering judgment to ensure reliability and quality.

Stay current with emerging AI models, frameworks, and developer tools.

Business & Cross-Functional Collaboration

Work directly with Product, Data Science, Marketing, Customer Experience, Merchandising, Operations, Finance, and other business teams.

Translate business problems into practical technical solutions.

Present technical decisions and project outcomes to senior leadership.

Own projects from initial concept through production and measurable business results.

Required Qualifications

Software Engineering

3–6 years of professional software engineering experience building and shipping production systems.

Strong proficiency in at least one of: Python, TypeScript, Java, Go, or C#.

Strong understanding of software design, OOP, SOLID principles, design patterns, and architecture.

Strong experience with SQL and relational databases, including schema design, indexing, query optimization, and transactions.

Experience with RESTful APIs and system integrations.

Experience writing meaningful unit, integration, and end-to-end tests.

Experience with at least one major cloud platform: AWS, GCP, or Azure.

Familiarity with Docker, CI/CD, and Git.

AI & LLM Experience

Active, hands-on use of AI coding assistants in software development.

Experience building or integrating at least one LLM-powered feature or workflow.

Understanding of prompt design, structured outputs, and basic LLM application patterns.

Ability to test, validate, and critically evaluate AI-generated results.

Genuine curiosity about emerging AI tools and technologies.

Preferred Qualifications

Experience with RAG, embeddings, or vector databases such as Pinecone or pgvector.

Experience with LangChain, LlamaIndex, or similar AI frameworks.

Familiarity with ML concepts such as embeddings, evaluation, or fine-tuning.

Experience with microservices and event-driven architectures.

Experience with observability tools such as Datadog, Grafana, or OpenTelemetry.

Knowledge of application security and OWASP best practices.

Experience with Agile/Scrum environments.

Open-source contributions or a public engineering portfolio.

Technology Environment

Languages: Python, TypeScript, Java, Go, SQL

Databases: PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, pgvector

Cloud & Infrastructure: AWS, GCP, Azure, Docker, Kubernetes, Terraform

APIs: REST, GraphQL, gRPC, OpenAPI

AI & LLM: OpenAI, Anthropic Claude, Gemini

AI Development Tools: GitHub Copilot, Cursor, Claude Code

Data & Streaming: dbt, Airflow, Spark, Kafka

Observability: Datadog, OpenTelemetry, Prometheus, Grafana

What Success Looks Like

You will be successful when you:

Ship reliable, production-quality software.

Deploy AI capabilities that solve real business problems.

Improve engineering velocity and quality through effective use of AI.

Take ownership from problem definition through production.

Deliver measurable improvements in revenue, cost, customer experience, or operational efficiency.

Communicate effectively with both technical and non-technical stakeholders.

Make sound decisions about when to use AI — and when not to use it.

What We Offer

Competitive, top-quartile engineering compensation.

Premium AI development tools provided from day one.

Annual learning and development budget.

Dedicated time for experimentation with emerging technologies.

Equity participation.

Comprehensive health, dental, vision, and wellness benefits.

Direct access to executive leadership.

A high-performing engineering environment where your ideas and work have visible impact.

This is an opportunity to build production software, deploy AI where it matters, and help shape how a growing company uses AI to operate and compete.