AI Engineering Manager
RemoteUnited States or Colombia
Job Summary
Lead end-to-end project delivery with clear governance, stakeholder communication, and accountability for outcomes. Build and mentor a high-performing AI engineering team while establishing technical standards and fostering a culture of quality and pragmatism. Own proposals and new business initiatives by defining technical feasibility and communicating risks and tradeoffs clearly to clients. Guide the design and delivery of RAG systems, agentic frameworks, and LLM-powered solutions that are robust enough for production. Run feasibility assessments to choose the right approach for each problem: prompting, RAG, fine-tuning, or classical ML. Design evaluation frameworks including LLM-as-a-judge approaches, metric creation, and go/no-go gates. Build scalable inference infrastructure and CI/CD pipelines for AI/ML models that support rapid iteration and reliable deployment. Automate the full MLOps/LLMOps lifecycle: tracking, versioning, deployment, monitoring, and retraining across the team.
Required Qualifications
- 7+ years building and deploying AI solutions in production environments
- 2+ years of direct team leadership or technical management experience
- Expert Python proficiency
- Strong Git practices
- Experience with ML/LLM versioning and deployment
- Solid cloud experience across AWS, Azure, or GCP
- Containerisation knowledge
- Orchestration knowledge
- Hands-on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation
- Proven MLOps/LLMOps track record using tools like MLflow, Weights and Biases, or similar
- Practical evaluation design skills: metrics, dataset curation, and structured experimentation
- Experience with event-driven architectures
- Experience with APIs
- Experience with microservices
- A clear communicator equally comfortable with engineering teams and senior stakeholders
- Strong hiring and team-building instincts
- Proven mentoring experience
- English: Advanced
- 7+ years of hands-on AI/ML engineering experience in production environments
- 2+ years of direct team leadership or technical management responsibility
Desired Qualifications
- preference for Azure
- Databricks MLOps platform
- LLM fine-tuning experience
- Building agentic GenAI systems
- Infrastructure as Code
- Security and observability for AI services
- Classical ML background
- Open-source contributions
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