AI Engineer

• Strong passion for Generative AI, LLMs, and AI-powered products.
• Strong software engineering fundamentals.
• Experience coding in Python.
• Experience working with APIs, Git, SQL, and backend development concepts.
• Experience building LLM-based applications, agents, workflows, or automations.
• Understanding of agentic AI patterns and orchestration frameworks.
• Understanding of RAG architectures, vector databases, embeddings, retrieval strategies, and context optimization.
• Understanding of prompt engineering techniques, LLM behavior, structured reasoning, and token optimization.
• Ability to design evals, tests, monitoring processes, and feedback loops for AI systems.
• Strong ownership, autonomy, and ability to move projects forward with limited supervision.
• Ability to research independently, compare alternatives, and recommend practical solutions.
• Ability to explain technical concepts clearly and teach others.
• High adaptability to evolving requirements, timelines, tools, and priorities.

We are looking for someone able to

• Design, build, and iterate AI-powered features, agents, workflows, automations, and internal tools.
• Build agentic AI systems using frameworks or similar orchestration tools.
• Design and implement RAG systems, including vector databases, GraphRAG, hybrid retrieval, agentic RAG, and retrieval optimization.
• Create, test, and optimize prompts, system instructions, context strategies, token usage, and AI interaction patterns.
• Develop evaluation frameworks to measure quality, reliability, accuracy, recall, precision, safety, and performance.
• Implement observability and monitoring using tools and platforms.
• Create guardrails, fallback strategies, safety mechanisms, and human-in-the-loop workflows.
• Build prototypes, proof of concepts, reusable templates, and production-ready AI components.
• Research new AI tools, frameworks, models, infrastructure, and healthcare AI trends.
• Collaborate with product, design, engineering, QA, DevOps, and commercial teams to define feasible AI solutions.
• Support AI discoveries, technical validations, architecture decisions, risk assessments, and effort estimations.
• Document best practices, teach other team members, and help teams adopt AI effectively

Other valuable skills

• Experience with LangChain, LangGraph, LlamaIndex, OpenAI, Anthropic, Gemini, AWS Bedrock, or similar tools.
• Experience with Langfuse, LangSmith, Datadog, or other observability platforms.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, pgvector, or similar.
• Experience with GraphRAG, knowledge graphs, hybrid search, semantic search, or agentic RAG.
• Experience creating automated evaluations, regression tests, prompt tests, retrieval tests, and quality benchmarks.
• Experience with automation tools such as n8n, Make, Zapier, Retool, or similar.
• Experience with FastAPI or other Python backend frameworks.
• DevOps knowledge, including Docker, CI/CD, cloud services, deployment workflows, monitoring, and infrastructure basics.
• Previous healthcare, biotech, or healthtech experience.
• Familiarity with HIPAA, PHI, healthcare interoperability, EHR integrations, FHIR, or HL7.