Principal AI Engineer - United States

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Key Responsibilities

AI Engineering & System Design

• Design, build, and operate AI-powered applications, including LLM-based services, ML-driven workflows, and intelligent automation.

• Integrate AI capabilities into Java-based backend systems and cloud-native platforms.

• Design scalable API-first services (REST & GraphQL) exposing AI capabilities across products.

• Implement data pipelines supporting feature engineering, retrieval-augmented generation (RAG), vector search, and inference.

• Apply best practices for prompt design, model orchestration, evaluation, and observability.

Cloud & Platform Engineering (AWS - Must Have)

• Build and operate cloud-native AI systems on AWS, including EC2, S3, RDS, Lambda, and EKS.

• Design containerized workloads using Docker and Kubernetes (EKS).

• Optimize systems for scalability, latency, reliability, and cost efficiency.

• Implement Infrastructure as Code using Terraform or AWS CDK.

Data & Distributed Systems

• Design and operate relational (SQL) and NoSQL data stores for high-scale, distributed systems.

• Make informed trade-offs around data consistency, availability, and performance.

• Work with event-driven and asynchronous architectures where appropriate.

Technical Leadership & Impact

• Lead complex technical initiatives end-to-end, from design through production deployment.

• Influence system design and engineering standards across teams through design reviews and technical guidance.

• Mentor senior engineers and raise the overall bar for AI and cloud engineering excellence.

• Collaborate with Product, Data, UX, Security, and DevOps teams to deliver AI-driven product capabilities.

Qualifications and Skills

Required (Must Have)

• 8-10 years of hands-on software engineering experience building large-scale, production systems.

• Strong, hands-on experience with Java in backend and distributed systems.

• Mandatory, hands-on experience with AWS, including designing and operating cloud-native workloads.

• Strong experience with SQL and NoSQL databases in production environments.

• 3+ years of experience building AI-powered applications, including ML or LLM-based systems. • Experience with API-first architectures (REST, GraphQL).

• Hands-on experience with Docker and Kubernetes (EKS).

• Strong problem-solving skills and ability to own systems end-to-end.

Nice to Have

• Experience with Generative AI platforms and frameworks (AWS Bedrock, OpenAI APIs, LangChain, LlamaIndex).

• Experience with vector databases and semantic search.

• Familiarity with MLOps practices, model monitoring, and evaluation frameworks.

• Experience working in product-driven, agile environments.

Leveling Guidance

• Senior AI Engineer: Owns complex components and services; strong execution and technical depth.

• Principal AI Engineer: Owns multi-team technical initiatives; influences architecture and engineering standards across the organization.

Why Join Us?

• Real AI Impact: Build AI systems that ship, scale, and deliver customer value.

• Hands-On Leadership: Lead through deep technical contribution.

• Modern Stack: Java, AWS, Kubernetes (EKS), SQL/NoSQL, and Generative AI.

• Collaboration: Work with strong product, data, and engineering partners.

• Core Values: Be part of a company that lives by Shattering Boundaries, Sparking Greatness, and Sharing Success.