Lead AI Engineer

Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI Engineering workstream for the Luma platform. This is a hands-on technical leadership role responsible for driving the architecture, design, and delivery of enterprise-scale Agentic AI solutions while serving as the primary technical interface for the client. The ideal candidate will combine deep expertise in AI engineering, distributed systems, cloud-native architectures, and MLOps with exceptional stakeholder management skills. This individual will oversee multiple engineering pods, mentor technical teams, drive engineering excellence, and partner closely with client leadership to shape the AI roadmap and ensure successful delivery. Key Responsibilities Lead AI architecture and engineering roadmap for Agentic AI platforms. Design and deliver scalable, production-grade AI solutions. Oversee AI platform services, backend APIs, microservices, MLOps, observability, and cloud infrastructure. Partner with clients to translate business needs into AI solutions and lead architecture discussions. Mentor AI engineers, conduct design/code reviews, and drive engineering best practices. Lead multiple engineering teams, manage delivery, risks, and technical roadmaps. Evaluate and adopt emerging AI technologies and frameworks. Required Skills AI/ML: GenAI, LLMs, Agentic AI, Multi-Agent Systems, RAG, Prompt Engineering, AI Guardrails, MLOps. Programming: Python (expert), Golang, REST APIs, Async Programming. Cloud: AWS (Bedrock/AgentCore preferred), Lambda, ECS/EKS, API Gateway, Step Functions, S3, DynamoDB, CloudWatch. Backend: Microservices, Docker, Kubernetes, Distributed Systems. Leadership: Client-facing consulting, architecture design, stakeholder management, mentoring, and technical leadership. Qualifications 10–15+ years in software engineering with 5+ years leading AI/ML engineering teams. Experience building and deploying enterprise AI platforms on AWS. Strong client-facing, solution architecture, and cross-functional leadership experience. Preferred AWS Bedrock, LangGraph, CrewAI, AutoGen, AI Copilots, AI Observability, Enterprise SaaS, and large-scale distributed systems. Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

Lead the end-to-end AI engineering workstream for the Luma platform, including architecture, design, and delivery of enterprise-scale Agentic AI solutions. Oversee multiple engineering pods, mentor technical teams, and serve as the primary technical interface for clients.

Requires 10-15+ years of software engineering experience with at least 5 years leading AI/ML teams. Candidates must have deep expertise in AWS cloud-native architectures, distributed systems, and modern AI frameworks.

• KubernetesSouhaitée
• GoSouhaitée
• DockerSouhaitée
• Amazon Web ServicesSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• GenAI
• LLMs
• Agentic AI
• Multi-Agent Systems
• RAG
• Prompt Engineering
• Python
• Golang
• AWS
• Microservices
• Docker
• Kubernetes
• Distributed Systems
• MLOps
• Stakeholder Management
• Architecture Design
• Cloud-Native Architecture
• Langgraph
• MLOps (Machine Learning Operations)
• Generative Artificial Intelligence
• Observability
• CrewAI
• AutoGen
• Go (Programming Language)
• Technical Leadership
• AWS Bedrock
• Application Programming Interface (API)
• Artificial Intelligence
• Amazon Web Services
• Architectural Design
• Software As A Service (SaaS)
• Cloud Infrastructure
• Code Review
• Consulting
• Amazon DynamoDB
• Leadership
• Scalability
• Python (Programming Language)
• Machine Learning
• Mentorship
• RESTful API
• Software Engineering
• Solution Architecture
• Amazon CloudWatch
• API Gateway
• Docker (Software)
• Artificial Intelligence Strategy
• Artificial Intelligence Infrastructure

• Technology
• Software
• Data & Analytics
• Engineering
• Consulting
• Artificial Intelligence Engineer
• Artificial Intelligence Engineer (General)
• Software Developers

Expérience minimale

10+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Exigences de lieu

Country, Canada