Design, implement, and maintain production AI services using AWS native technologies.
Build and operate retrieval augmented generation (RAG) pipelines.
Engineer LLM enabled APIs and workflows that integrate directly into enterprise applications.
Develop solutions for unstructured data and document intelligence.
Apply strong software engineering practices ensuring AI systems meet requirements for performance, scalability, security, cost efficiency, and resilience.
Partner with platform and operations teams to support production readiness and monitoring of AI workloads.
Collaborate closely with Architecture, Data, Platform, and Product teams.
Provide technical leadership through implementation, code reviews, and design guidance for AI related initiatives.
Mentor engineers and teams on applied AI engineering patterns and responsible AI practices.
Ensure AI solutions adhere to enterprise governance, security, privacy, and model risk standards.
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
10+ years of experience in software engineering, with 3–5+ years focused on AI/ML, data intensive, or intelligent systems.
2–3+ years of hands on experience delivering AI/ML solutions on AWS.
Demonstrated experience with enterprise scale LLM based systems, including retrieval augmented generation (RAG) and vector search.
Strong proficiency in cloud native, serverless, and event driven architectures.
Experience with MLOps / DataOps concepts, infrastructure as code, and production observability.
Deep technical expertise in software architecture, cloud computing, microservices, API design, and data architecture.
Expertise in cloud native and serverless integration patterns.
Strong understanding of governance, metadata management, catalogs, lineage, and access controls.
Hands on experience with unstructured data and document intelligence solutions.