Senior Engineer – AI/ML Strategy & Delivery

Matrix Global

9d

About The Position

We are seeking a Senior AI/ML Engineer to lead the strategic implementation of generative AI and machine learning capabilities across enterprise platforms. This senior individual contributor role requires deep technical expertise in large language models, cloud-based AI services, and advanced ML engineering practices. The ideal candidate will combine hands‑on engineering proficiency with strategic thinking to architect and deliver production-scale AI systems that drive measurable business impact. This role sits at the forefront of AI innovation—developing cutting‑edge solutions, shaping enterprise AI strategy, and ensuring alignment with responsible AI and regulatory standards.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Mathematics, or a related technical field.
• Minimum 5+ years of hands‑on AI/ML engineering experience, with 3+ years directly focused on generative AI and LLM-driven applications.
• 5+ years of senior‑level or executive‑facing leadership experience in highly regulated industries, with the ability to influence senior stakeholders and drive enterprise‑scale initiatives.
• Expert proficiency in Python, including ML frameworks (PyTorch, TensorFlow) and LLM orchestration frameworks (LangChain, LlamaIndex).
• Deep experience with Azure OpenAI Service, Azure ML Studio, Databricks MLflow, and Google Vertex AI for enterprise model development, deployment, and monitoring.
• Strong understanding of MLOps/LLMOps practices including CI/CD for ML (Azure DevOps, GitHub Actions), infrastructure‑as-code (Terraform), and containerization (Docker, Kubernetes).
• Experience building real‑time inference architectures, streaming ML systems (Kafka, Pub/Sub), and edge AI deployment for latency‑sensitive use cases.
• Hands‑on experience with multi‑modal models, computer vision frameworks, and advanced NLP techniques beyond typical LLM text applications.

Responsibilities

• Design and deliver end‑to‑end generative AI solutions using cloud AI services such as Azure AI and Google AI to enable transformative business capabilities.
• Lead development and optimization of production-grade LLM applications, leveraging techniques such as RAG (Retrieval Augmented Generation), prompt engineering, model fine‑tuning, grounding, and multi‑agent architectures.
• Implement AI security controls, including prompt injection defense, adversarial attack mitigation, data poisoning detection, and prompt shielding.
• Build and deploy systems for content filtering, output monitoring, and automated AI safety guardrails for generative models.
• Architect scalable MLOps and LLMOps pipelines supporting model versioning, automated retraining, observability, explainability, and high availability (99.9% uptime).
• Partner closely with business stakeholders to translate strategic objectives into AI/ML proof‑of-concepts and production solutions, demonstrating ROI through rapid prototyping and iterative delivery.
• Drive enterprise-wide AI/ML technical strategy across a hybrid cloud landscape, evaluating emerging approaches including small language models, agentic AI, and edge inference strategies.
• Mentor platform engineers and data scientists on advanced ML methodologies, LLM techniques, and responsible AI practices through hands‑on collaboration.
• Perform technical evaluations and due diligence on AI vendors and tools, providing recommendations on technologies such as Cohere, Anthropic, and open‑source LLM ecosystems.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level