Databricks MLOps Engineer

We are looking for a Databricks MLOps Engineer to design, build, and operate cloud-native infrastructure that powers AI and data workloads at scale. You'll work at the intersection of platform engineering and AI — building the pipelines, deployment workflows, and observability layers that make machine learning models reliable, cost-efficient, and production-ready.

This is a hands-on engineering role. You'll be writing infrastructure-as-code, building data pipelines, integrating LLMs into production systems, and collaborating closely with AI and data engineers to keep the platform performing as the workloads grow.

What you'll do

• Design, implement, and maintain a cloud-native platform to support AI and data workloads, with a focus on Databricks and AWS Bedrock.
• Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics use cases.
• Develop infrastructure-as-code using CloudFormation and AWS CDK to ensure repeatable, secure deployments.
• Integrate AI models and LLMs into production systems, including RAG architectures and model serving workflows.
• Drive observability best practices — monitoring, alerting, and logging across AI platforms.
• Collaborate with AI engineers, data engineers, and platform teams to improve performance, reliability, and cost-efficiency of models in production.
• Contribute to the design and evolution of the AI platform to support new ML frameworks, workflows, and data types.
• Stay current with emerging tooling and recommend improvements to architecture and operations.

Basic qualifications

• 7+ years of professional experience in software and infrastructure engineering.
• Extensive experience building and maintaining AI/ML infrastructure in production — model deployment, lifecycle management, and serving workflows.
• Production-level experience with Databricks and MLflow — model registration, versioning, asset bundles, and serving.
• Strong knowledge of AWS and infrastructure-as-code, with AWS CDK experience specifically.
• Expert-level coding skills in both Python and TypeScript — building robust APIs and backend services.
• Strong understanding of containerization with Docker and hands-on CI/CD pipeline experience.
• Proven ability to design reliable, secure, and scalable infrastructure for real-time and batch ML workloads.
• Strong communication and collaboration skills — able to articulate technical decisions clearly to both engineering and non-technical stakeholders.

Preferred qualifications

• Familiarity with DSPy or similar LLM orchestration frameworks for programmatic prompt pipelines.
• Experience with LLM cost monitoring, latency optimization, and usage analytics in production.
• Knowledge of vector databases and embedding stores — OpenSearch or similar — to support semantic search and RAG architectures.
• Experience with ECS or other container orchestration tools.

When you join Solvd, you'll…

• Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation.
• Be part of a global team with equal opportunities for collaboration across continents and cultures.
• Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.

Ready to make an impact?

If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together.