- Company Name
- Altus Group
- Job Title
- Lead AI Engineer
- Job Description
-
**Job Title:** Lead AI Engineer
**Role Summary**
Lead end‑to‑end design, development, and production deployment of AI/ML capabilities for a commercial real estate SaaS platform, driving both LLM‑powered features and custom domain models while establishing AI standards, infrastructure, and best practices across the organization.
**Expectations**
- 8+ years product‑engineering experience; 3+ years in production AI/ML.
- Proven track record of training, evaluating, and deploying custom ML models in production.
- Hands‑on coding and training model pipelines; active participant in research and publications.
- Leadership of technical initiatives, cross‑functional collaboration, and mentoring.
- Strong balance of rapid innovation with responsible AI governance, risk management, and safety.
**Key Responsibilities**
- Architect and implement AI‑powered features (agentic workflows, data extraction, analysis).
- Lead R&D of custom AI/ML models for commercial real estate; evaluate fine‑tuning vs. from‑scratch.
- Set technical standards, patterns, and best practices for AI/ML across feature teams.
- Build LLM integrations, Retrieval‑Augmented Generation (RAG), and multi‑agent orchestration.
- Design training pipelines, experiment tracking, model versioning, and inference infrastructure.
- Decide on build‑vs‑buy for AI tooling; manage GPU resources and scalable serving.
- Partner with engineering, product, and data teams to translate business requirements into AI solutions.
- Mentor engineers on ML techniques, prompt engineering, and agentic frameworks.
- Drive AI roadmap, research initiatives, and internal knowledge sharing (e.g., AI Guild).
- Conduct proofs‑of‑concept on emerging AI technologies.
- Establish experimentation frameworks with A/B testing for AI features.
- Contribute to AI/ML community via publications, blogs, or open‑source projects.
- Define governance, quality gates, testing strategies, and safety measures for AI systems.
- Produce documentation and runbooks for reliable AI operations.
**Required Skills**
- Expertise in neural networks, transformers, diffusion models, graph neural networks, or reinforcement learning.
- Proficient with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Experience with LLM patterns: RAG, prompt engineering, fine‑tuning, agentic architectures.
- Advanced understanding of distributed training, GPU optimization, and experiment tracking tools.
- Strong software engineering fundamentals: system design, APIs, cloud architecture.
- Knowledge of vector databases, embeddings, semantic search, and feature stores.
- Proven MLOps experience: monitoring, A/B testing, shadow deployments, versioning.
- Cloud familiarity (AWS, Azure, or GCP) for scalable ML workloads.
- Solid foundations in statistics, probability, and mathematical optimization.
- Excellent technical communication and collaborative leadership skills.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or related field (advanced degrees preferred).
- Certifications in cloud ML services (e.g., AWS TensorFlow Developer, Azure AI Engineer) are a plus.