Senior AI Engineer, Platform Engineering

• Design, build, and deploy AI agents and agentic workflows that solve business and engineering challenges using modern LLM frameworks.
• Develop AI-powered applications leveraging Retrieval-Augmented Generation (RAG), vector databases, embeddings, tool calling, and agent orchestration patterns.
• Optimize retrieval quality and response accuracy through chunking strategies, metadata enrichment, hybrid search, reranking, evaluation, and continuous improvement.
• Integrate AI solutions with enterprise platforms such as GitHub, Jira, Confluence, Datadog, Slack, Kubernetes, and internal APIs.
• Develop reusable connectors, tools, and agent capabilities that enable agents to retrieve information and perform actions across systems.
• Establish best practices for testing, evaluation, observability, security, and governance of AI applications.
• Monitor and optimize agent performance, reliability, latency, accuracy, and cost while troubleshooting production issues and continuously improving solution quality.

• 5+ years of experience in Software Engineering, Platform Engineering, or Cloud Engineering
• Hands-on experience building AI applications using frameworks such as LangGraph, Strands Agents, OpenAI Agents SDK, or similar agent orchestration frameworks.
• Strong programming skills in TypeScript, Go and/or Python
• Experience designing and building microservice applications
• Experience integrating APIs and enterprise systems
• Hands-on experience building production AI applications using LLMs Strong understanding of:

• Vector databases and embeddings
• Tool calling and agent orchestration
• Structured outputs, context engineering, and agent orchestration
• AI evaluation and observability Preferred Qualifications:
• Experience building AI copilots, digital assistants, or autonomous agents
• Experience integrating AI solutions with GitHub, Jira, Slack, Datadog, Confluence, or similar enterprise platforms
• Experience with vector databases such as OpenSearch
• Experience with AI observability and evaluation tools such as Langfuse or Datadog LLM Observability
• Experience building MCP servers and agent interoperability patterns
• Experience with Kubernetes and cloud-native platforms What Success Looks Like:
• Deliver production-ready agentic AI solutions that solve real business and engineering challenges
• Build reusable AI workflows, tools, and integrations that accelerate adoption across teams
• Improve productivity and operational efficiency through intelligent automation
• Drive measurable outcomes through scalable, secure, and reliable AI applications

Joining us is more than saying “yes” to making the world a healthier place.

It’s discovering a career that’s challenging, supportive and inspiring.

Where a culture driven by excellence helps you not only meet your goals, but also create new ones.

We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates.

If this sounds like the workplace for you, apply now!

We commit to respond to every applicant.