Senior AI-Driven Backend Engineer

Harnham; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Harnham is seeking a senior backend engineer to lead the integration of AI capabilities into its SaaS platform. This hands-on role focuses on backend architecture, AI service delivery, and bringing ML solutions from prototype to production.

Responsibilities include designing services, integrating LLMs and RAG, collaborating with data science to productionize models, and building reusable AI infrastructure. You will drive architectural decisions and ensure scalable, secure systems.

Qualifications

• 8+ years of software engineering experience.
• Experience integrating AI/ML capabilities into commercial or customer-facing software products.

Responsibilities

• Design, build, and enhance backend services within an existing SaaS platform.
• Integrate AI and machine learning capabilities including LLMs, RAG, model serving, predictions, and scoring services.
• Partner with Data Science teams to transition models and prototypes into production environments.
• Develop reusable infrastructure, frameworks, and patterns for future AI initiatives.
• Lead complex technical projects from architecture and design through deployment.
• Evaluate emerging AI technologies and guide architectural and build-versus-buy decisions.
• Improve platform scalability, performance, reliability, security, and maintainability.
• Communicate technical recommendations and tradeoffs to engineering leadership and stakeholders.

Skills

AI integration

Backend development

Distributed systems

Cloud environments

CI/CD & monitoring

Security best practices

Python

FastAPI

Tools

Python

FastAPI

MLflow

LangChain

Vector Databases

RAG

LLM APIs

Model Serving

Job description

Harnham is seeking a senior backend engineer to lead the integration of AI capabilities into its SaaS platform. This hands-on role focuses on backend architecture, AI service delivery, and bringing ML solutions from prototype to production.

Responsibilities include designing services, integrating LLMs and RAG, collaborating with data science to productionize models, and building reusable AI infrastructure. You will drive architectural decisions and ensure scalable, secure systems.