Engineering Manager – AI Engineering & LLM Systems

Roles & Responsibilities

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.

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.

Qualifications

Required Experience

• 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)

Tell employers what skills you have

Ai
Generative AI Application Development and Deployment
AI Agents
Technology Expertise
Extensive Work Experience
Leading Development Teams
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