#req11000
ns that create meaningful business impact.
In this role you will...
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.
You've got what it takes if you have...
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.
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