Senior AI Backend Engineer

About the role:

We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems.

What you'll be doing:

As a Senior Backend Engineer in the AI Engineering team, you will:

• Build and maintain reliable, scalable backend services to support AI agent execution and orchestration.
• Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse.
• Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama.
• Build and maintain integrations with clinical systems (FHIR, EMR).
• Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse.
• Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes.
• Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems.
• Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities.

What we're looking for:

• 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin).
• Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines.
• Proven experience in building and scaling backend APIs, microservices, and background jobs.
• Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema design, data modeling, and query optimization.
• Experience with message brokers and distributed systems (e.g., Pub/Sub, Redis Streams, RabbitMQ).
• Highly adaptable, a strong team player, with the ability to quickly learn and apply new technologies.

Advantages:

• Strong proficiency in Python and/or Node.js/NestJS.
• Experience with clinical systems and healthcare data standards (FHIR, EMR/EHR).
• Hands-on experience with AI agent frameworks such as LangChain, LangGraph, or LiteLLM.
• Experience orchestrating hybrid model stacks combining commercial APIs (OpenAI, Google Gemini) with self-hosted or fine-tuned LLMs.
• Familiarity with observability tools for AI systems (Langfuse, OpenTelemetry).