Senior AI Infrastructure Engineer, Databricks, AWS, Python

October 23

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Solvd, Inc.

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SaaS • B2B • Enterprise

Solvd, Inc. is a global software engineering and consulting company that delivers comprehensive end-to-end solutions. Founded in 2011, Solvd offers core engineering services, including software development for web and mobile platforms, digital experience and design, data and AI/ML solutions, and cloud platform modernization. The company is an AWS partner and is known for optimizing resources, solving complex problems, and enhancing user satisfaction. Solvd emphasizes innovation and quality assurance, employing over 800 international professionals across 8 offices worldwide. The company prides itself on transforming businesses by providing feature-rich digital products, manual testing, automation, and employing cutting-edge technology solutions. Their proprietary tools like Zebrunner and Carina aid in improving development and QA processes. Solvd operates with a focus on collaboration, top talent cultivation, and customized technical solutions tailored to individual client needs, serving clients across 15 countries.

501 - 1000 employees

Founded 2010

☁️ SaaS

🤝 B2B

🏢 Enterprise

📋 Description

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

🎯 Requirements

• 7+ years of professional experience in software engineering and infrastructure engineering. • Extensive experience building and maintaining AI/ML infrastructure in production, including model, deployment, and lifecycle management. • Strong knowledge of AWS and infrastructure-as-code frameworks, ideally with CDK. • Expert-level coding skills in TypeScript and Python building robust APIs and backend services. • Production-level experience with Databricks MLFlow, including model registration, versioning, asset bundles, and model serving workflows. • Expert level understanding of containerization (Docker), and hands on experience with CI/CD pipelines, orchestration tools (e.g., ECS) is a plus. • Proven ability to design reliable, secure, and scalable infrastructure for both real-time and batch ML workloads. • Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. • Strong collaboration skills and the ability to partner effectively with cross-functional teams. • Familiarity with emerging LLM frameworks such as DSPy for advanced prompt orchestration and programmatic LLM pipelines. • Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments. • Knowledge of vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG.

🏖️ Benefits

• 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.