Staff AI Engineer

About the role

Safe Software is looking for a Staff AI Engineer to design, build, and deploy production‑grade AI systems across the organization. This hands‑on role covers the full AI lifecycle—from data preparation and model development to evaluation, deployment, monitoring, and continuous improvement.

Key responsibilities

• Design, build, evaluate, deploy, and operate end‑to‑end AI/ML systems in production, including data pipelines, model training, integration, and monitoring.
• Architect and implement agentic and multi‑agent systems with orchestration, task routing, tool use, human oversight, and failure recovery.
• Create enterprise knowledge and retrieval solutions using embeddings, hybrid search, reranking, and access‑controlled retrieval.
• Integrate AI solutions with enterprise applications, APIs, databases, and governed tools.
• Establish automated testing, evaluation, and observability for model quality, hallucination risk, latency, cost, drift, and regression.
• Design secure, responsible AI systems with least‑privilege access, auditability, and safeguards against prompt injection and data leakage.
• Develop reusable architectures, libraries, and engineering standards while providing technical leadership and mentorship.
• Evaluate emerging LLMs, frameworks, and platforms and make evidence‑based adoption recommendations.

Required profile

• 8+ years of software engineering and AI/ML experience, including 3+ years building and operating AI/ML systems at scale.
• Strong software engineering skills in Python or comparable backend technologies.
• Proven experience developing, fine‑tuning, evaluating, deploying, and monitoring AI or machine‑learning models.
• Applied AI experience in enterprise use cases such as chatbots, workflow automation, RAG, intelligent document processing, recommendation systems, or decision support.
• Deep understanding of generative AI, LLMs, retrieval systems, agent‑based architectures, and applied machine learning.
• Experience with production data pipelines, APIs, model‑serving infrastructure, testing, security, reliability, and observability.

Required skills

• Python
• LangGraph, Semantic Kernel, AutoGen, CrewAI (or equivalent orchestration tools)
• Vector databases, embeddings, semantic or hybrid search, reranking
• Databricks, Snowflake, Amazon Bedrock, Microsoft Azure AI platforms
• MCP, A2A, self‑hosted or open‑weight models, hybrid AI architectures

What we offer

• Meaningful work with impact across the business and product.
• Supportive environment with high autonomy and team collaboration.
• Flexible remote‑friendly work arrangements and work‑life balance.
• Annual learning budget, training programs, and profit‑sharing.
• Extended health, dental, wellness benefits from day 1, plus parental leave top‑up.