Senior AI Engineer

Quick Facts

• Role: Senior AI Engineer

Description

Senior AI Engineer to build and operate production AI systems end-to-end. You will create agentic and multimodal applications, LLM workflows, and RAG pipelines, integrate AI with engineering/manufacturing and business systems, and run Python services on Azure. The role also emphasizes repeatable evaluations to improve accuracy, reliability, latency, and cost, along with mentoring and shaping technical direction.

Responsibilities

• Own AI applications and reusable services from prototyping through integration, production deployment, monitoring, and support

• Build agents, multimodal applications, LLM workflows, and RAG pipelines using prompt design, tool calling, structured outputs, embeddings, and hybrid search

• Ingest and parse messy inputs (datasheets, schematics, test logs, media, business data) to deliver grounded AI capabilities

• Integrate AI with engineering tools, manufacturing/test systems, and business applications via APIs and MCP servers with validation, security, and human oversight

• Apply classical ML (classification, anomaly detection, computer vision, audio processing) and deploy/monitor models alongside LLM systems

• Develop repeatable evaluations to improve retrieval and answer quality, accuracy, reliability, latency, and cost

• Develop and operate Python services on Azure using PostgreSQL, Terraform, containers, CI/CD, and observability

• Collaborate on requirements and priorities; mentor engineers through code and design reviews

Requirements

• 5+ years of software engineering experience, including delivering and supporting production LLM applications beyond proof-of-concept

• Strong Python and backend skills (API design, testing, debugging, maintainable software)

• Hands-on experience with LLM APIs, prompt design, and tool-enabled agents (LangChain, LangGraph, or equivalents)

• Practical RAG experience (embeddings, vector/hybrid search, reranking, measuring retrieval and answer quality)

• Solid ML fundamentals; ability to ship non-LLM models to production using PyTorch, scikit-learn, NumPy, and pandas

• Cloud deployment experience (preferably Azure) using containers, CI/CD, infrastructure as code, and monitoring

• Strong SQL skills (preferably PostgreSQL) and understanding of authentication, access control, and secure data handling

• Clear communication of technical trade-offs; ability to work independently and mentor others

• Bachelor’s or Master’s in Computer Science/Engineering or equivalent experience

Benefits

• Hands-on ownership of AI solutions from problem framing through deployment and ongoing support