AI Engineer

Sony Interactive Entertainment invites you to join the D2C Data Science team in San Diego as an AI Engineer. This onsite role centers on designing, building, and operating production AI capabilities and automated workflows for SPOC and digital commerce, with a strong focus on applied AI engineering rather than model training.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 401(k) matching
• Paid time off
• Wellness program
• Employee discounts for Sony products
• Bonus package eligibility

Responsibilities

• Develop applied AI features by building services, workflows, and reusable components for LLM powered automation, retrieval, tool use, summarization, classification, decision support, and knowledge workflows.
• Partner with operations, product, data, risk, and engineering teams to translate business use cases into prototypes, measure outcomes, and advance proven capabilities into production.
• Design AI workflows that incorporate tool calls, structured outputs, workflow state, internal APIs, and human review patterns to take actionable steps while remaining auditable and controlled.
• Contribute to retrieval augmented generation and agentic retrieval pipelines over enterprise content and operational data using embeddings, vector databases, hybrid search, reranking, citations, access controls, and freshness strategies.
• Establish and maintain evaluation suites, regression tests, prompt and model versioning, trace analysis, guardrails, policy checks, PII handling, hallucination mitigation, and operational monitoring to improve AI quality and safety.
• Build scalable APIs, microservices, and event driven workflows in Python or Java with emphasis on reliability, security, cost efficiency, and clean integration with existing services.
• Deliver AI services in the cloud using AWS, containers, infrastructure as code, CI/CD, secrets management, observability, and operational runbooks.
• Collaborate across technical and non-technical teams in design reviews, planning, troubleshooting, documentation, and knowledge sharing.

Requirements

• Bachelor's degree in computer science, engineering, or a related technical field, or equivalent practical experience, plus 2+ years of professional software engineering experience.
• Hands-on experience building AI or generative AI features that connect model APIs to business workflows, data, documents, or internal services.
• Strong software engineering skills in Python and/or Java, including API development, testing, debugging, asynchronous processing, and maintainable service design.
• Experience with AWS or equivalent cloud services.
• Familiarity with embeddings, chunking, indexing, retrieval strategies, vector and hybrid search, reranking, citations, and vector stores such as OpenSearch, Pinecone, Weaviate, Redis, pgvector, Azure AI Search, or similar technologies.
• Experience with AI orchestration patterns and tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI Agents SDK, N8N, AWS Bedrock Agents and Knowledge Bases, or comparable tools.
• Experience designing prompts, schemas, tool/function calls, workflow contracts, and validation logic so AI systems can produce dependable outputs and interact safely with internal systems.
• Familiarity with tracing, monitoring, evals, prompt testing, quality metrics, and debugging tools such as LangSmith, Arize Phoenix, OpenTelemetry, Datadog, Splunk, New Relic, CloudWatch, or comparable platforms.
• Exceptional communication skills, able to translate business requirements into technical tasks, collaborate across teams, and explain AI tradeoffs in clear, practical terms.

Technologies

• Python
• Java
• AWS
• OpenSearch
• Pinecone
• Weaviate
• Redis
• pgvector
• Azure AI Search
• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
• OpenAI Agents SDK
• N8N
• AWS Bedrock
• LangSmith
• Arize Phoenix
• OpenTelemetry
• Datadog
• Splunk
• New Relic
• CloudWatch

Preferred Skills

• Model Context Protocol (MCP) or related patterns for connecting AI apps to enterprise tools, databases, documents, and workflows
• Multimodal AI systems including text, image, document, audio, or video models, multimodal embeddings, OCR/document understanding, or content moderation workflows
• Experience applying AI to commerce, fraud, payments, risk, customer support, marketplace operations, trust and safety, or digital commerce business processes