Senior MLOps Expert
(Remote)
6-Month Contract
Key Responsibilities
• Architect, design and implement cloud infrastructure on AWS that supports AI/ML/agentic-AI workloads.
• Lead infrastructure-as-code efforts using Terraform: create modules, manage environments, ensure reproducible deployments.
• Own the end-to-end MLOps lifecycle: model training, fine-tuning, deployment, monitoring, versioning, governance.
• Design, build and fine-tune chatbot solutions (AI-related) — from data ingestion, model selection, interface integration, to live production operations.
• Provide hands-on development of AI/ML components or agentic AI agents, collaborating cross-functionally with data scientists, engineers and product owners.
• Establish best practices for observability, performance tuning, cost optimisation and security for AI/ML infrastructure.
• Mentor and guide engineering teams on cloud-native architecture, IaC, MLOps, and AI solution delivery.
• Drive technical decision-making, produce architecture diagrams, create reference implementations, and enforce design standards.
• Operate in a remote mode, delivering reliably across time zones and providing frequent status updates to stakeholders.
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Must-Have Requirements
• Minimum 12 years of industry experience in software engineering, cloud architecture, or systems engineering.
• Demonstrated expertise in MLOps: building pipelines, deploying models, monitoring/operationalising ML/AI solutions.
• Strong hands-on experience with AWS, including services relevant to AI/ML, compute, storage, networking, security.
• Deep infrastructure automation with Terraform: writing modules, managing state, promoting reuse, controlling drift.
• Proven experience designing, building and fine-tuning chatbot systems (or comparable conversational/agentic AI solutions).
• Experience in AI/ML or GenAI or agentic AI (at least one of these domains) in production or near-production environments.
• Strong coding capability in relevant languages (Python, Java, or similar), and comfortable working in “architect-developer” mode.
• Excellent communication and collaboration skills for remote delivery across global teams.
• Comfortable working in contract mode with remote set-up and delivering high quality in a compressed timeframe.
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Preferred Qualifications
• Certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning, or Terraform Associate.
• Experience with vector databases, embeddings, retrieval-augmented generation (RAG) systems, agent frameworks.
• Experience with CI/CD for ML/AI (GitHub Actions, Jenkins, pipelines) and infrastructure monitoring/observability (CloudWatch, Prometheus, Grafana).
• Experience with secure production deployment of AI systems (governance, data quality, bias mitigation, ethics).
• Past contract experience and comfort working in high-velocity environments with ambiguous requirements.
Munesh
770-838-3829,
CYBER SPHERE LLC
