105 189
14 861
We are looking for an experienced Senior AI Engineer who demonstrates a high level of autonomy in designing full-stack solutions and can make a tangible impact on the development of a flagship medical assistant used by millions of doctors worldwide.
Our Client is an innovative organization that combines the stability of a mature company with the agility and culture of a startup. The project focuses on building a central Generative AI (GenAI) platform , enabling hundreds of product teams to create and deploy scalable AI agents.
???? WORK MODE: 100% remote
⏱ AVAILABILITY: We are looking for candidates available immediately or with a notice period of up to one month.
???????? WHAT WILL YOU BE DOING?
Designing, building, and operating production-grade LLM (Large Language Model) systems and AI agents, ensuring the highest quality standards.
Implementing modern GenAI patterns such as RAG (Retrieval-Augmented Generation) , routing, tool usage, and advanced agent orchestration.
Creating evaluation frameworks, including regression tests, A/B tests, and rubric-based qualitative assessments (e.g. ROUGE, BLEU).
Optimizing AI workloads for cost, latency, reliability, and minimizing hallucinations in mission-critical medical systems.
Implementing AI security and trust practices, including guardrails and system-level error mitigation.
Working closely with product, platform, and security teams to deliver end-to-end features.
???? WHAT WE EXPECT FROM YOU
Must-have:
Minimum 8 years of professional experience in software engineering, with a strong focus on Python and backend technologies.
Hands-on experience deploying LLM-based applications or agents to production environments, and confidence in live coding interviews.
Knowledge of frameworks such as LangChain , LangGraph , or equivalent agent-building tools, as well as Pydantic for data validation.
Experience with RAG pipelines , vector search (e.g. OpenSearch), and monitoring systems (Tracing, Observability).
Ability to build secure and reliable cloud systems using AWS, Azure, or GCP (Google Cloud Platform) .
Familiarity with CI/CD processes and Infrastructure as Code (IaC) practices.
Nice-to-have:
Experience optimizing performance and cost for large-scale LLM workloads.
Background in regulated environments compliant with SOC 2 or HIPAA standards.
Knowledge of AI security best practices and AI ethics.
???? WHY JOIN?
Stable employment in a team of 100+ talented engineers .
Real impact on patients’ health and lives by building tools that reduce diagnostic errors.
International work environment with high autonomy and opportunities to mentor others.
Exposure to a cutting-edge technology stack in the Generative AI space.
Thank you for all applications. We will contact selected candidates.