Backend AI Engineer

The role

This person will design, build, and own core AI infrastructure and services. They will build model-serving pipelines, inference and orchestration layers, data pipelines, and APIs to connect AI models to enterprise environments.

What you will do

• Design, build, and maintain backend services and APIs for GenAI, LLM, and Computer Vision model integrations.
• Build and own core AI/ML infrastructure including model-serving pipelines, inference services, data pipelines, and embedding/vector stores.
• Architect scalable, production-grade systems for real-time and batch AI workloads.
• Implement and optimize RAG systems, prompt/context pipelines, and orchestration layers.
• Build robust APIs, microservices, and integration layers connecting AI systems to customer and legacy data.
• Own the reliability, performance, and observability of backend AI systems.
• Collaborate with Forward Deployed Engineers, ML engineers, and product teams.
• Evaluate and integrate ML/CV/LLM models into production backend systems.
• Produce technical documentation including architecture diagrams, API specs, and runbooks.
• Mentor engineers and contribute to internal backend engineering best practices.

Required qualifications

• 4–8+ years of experience in backend software engineering, ML/platform engineering, or similar roles.
• Strong proficiency in TypeScript/Node.js.
• Strong API and microservice design skills.
• Hands-on experience building and operating production backend systems at scale.
• Experience integrating ML or Generative AI models into backend services.
• Solid understanding of cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Experience designing and operating data pipelines across structured and unstructured data.
• Hands-on experience building retrieval-augmented generation (RAG) systems and AI memory architectures.
• Strong grasp of system design fundamentals: scalability, reliability, security, and observability.
• Comfortable working cross-functionally with ML engineers, product, and customer-facing teams.
• Bachelor's degree (or higher) in Computer Science or a related field.

Nice to have

• Working proficiency in Python is a plus for ML/model integration work.
• Familiarity with ML frameworks (PyTorch, TensorFlow, OpenCV).
• Experience with MLOps tooling: model registries, feature stores, CI/CD for ML, and monitoring/observability for ML systems.
• Background in event-driven or real-time systems (Kafka, gRPC, WebSockets).
• Experience in industrial, IoT, or operational technology (OT) environments.
• Experience in startup or high-growth environments.

Benefits

• Innovative Environment
• Collaborative Culture
• Professional Growth
• Competitive Compensation: salary and equity package

About the company

Nexxa is building AI systems for heavy industries to enable machines, systems and operations to think, decide and act autonomously. Their mission is to translate deep technical breakthroughs into operational reality.