Engineering Manager – AI Engineering & LLM Systems

AICS builds Healthcare AI solutions that improve clinical workflows through large language models, agentic AI, and modern AI engineering.

We are looking for an Engineering Manager to lead a team of Machine Learning Engineers building production-ready LLM applications, AI infrastructure, and clinical AI systems.

Key Responsibilities

• Lead and grow a high-performing Machine Learning Engineering team.
• Drive the design, development, and deployment of production LLM applications and AI systems.
• Build scalable AI engineering workflows covering model evaluation, experimentation, deployment, and continuous improvement.
• Lead the development of agentic AI capabilities, including multi-agent workflows, tool integration, memory, and orchestration.
• Establish engineering best practices for AI development, software quality, testing, and MLOps.
• Work closely with AI Research, Product, and Software Engineering teams to translate research into production products.
• Continuously evaluate emerging AI technologies and adopt new techniques that improve product quality and engineering productivity.

Requirements:

• 8+ years of software engineering, machine learning engineering, or AI engineering experience.
• 3+ years leading technical engineering teams.
• Proven experience delivering AI products into production.

Technical Expertise

Candidates should have practical, hands-on experience with most of the following:

• Large Language Models (LLMs) and Generative AI application development
• Model fine-tuning or adaptation for domain-specific use cases
• LLM evaluation and benchmarking
• RAG and knowledge retrieval systems
• Agentic AI frameworks and workflow orchestration
• Prompt engineering and structured tool calling
• PyTorch and Hugging Face ecosystem
• AI deployment, inference optimization, and MLOps
• Cloud-native engineering (Docker, Kubernetes, Azure or GCP)

Skills

Ai, Generative AI Application Development and Deployment, AI Agents, Technology Expertise, Extensive Work Experience, Experimentation, Cloud Native Architecture, leading technical teams, Software Engineering, Domain Adaptation Techniques, AI Evaluation, MLOps, Hugging Face, PyTorch, LLMs, AI Safety, Hands-On Experience, Product Development, Deployment