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About This Role
Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn't just the Best Place to Play — it's also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we're part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Senior Software Engineer - AI & Agentic Architecture
This is a senior individual-contributor role combining deep hands-on engineering with multiple agentic frameworks & SDKs, harnesses, MCP, and APIs, technical leadership, and close collaboration with engineering, security, and product teams. You'll design and ship agentic systems, developer tooling, and reusable platform capabilities that improve productivity across SIE.
What you'll do:
Agentic & AI Engineering
- Design, build, and operate production-quality agentic applications using agentic SDKs/harnesses — including multi-agent orchestration, subagent delegation, tool integration, and lifecycle hooks.
- Design Model Context Protocol (MCP) tool and resource interfaces that give coding agents/harnesses safe, reliable access to backend systems and enterprise data.
- Engineer prompts for reliable structured output (JSON schemas, few-shot examples, validation/retry loops) and build evaluation frameworks to measure and improve output quality.
- Manage context effectively across long documents, multi-turn conversations, and multi-agent handoffs; design escalation and human-in-the-loop patterns for production reliability.
Developer Productivity
- Configure and extend Codex/Claude Code for team-wide use: AGENTS.md/CLAUDE.md hierarchies, custom slash commands, Agent Skills, path-specific rules, and plan mode.
- Integrate agentic development into CI/CD pipelines for automated code review, test generation, and PR feedback, tuned to minimize false positives and duplicate findings.
- Build and maintain MCP server integrations (project- and user-scoped) that extend agent-native development capabilities across engineering workflows.
- Identify high-value opportunities for AI-assisted development and design reusable capabilities that multiple teams can adopt, not just one-off solutions.
Discovery, Prototyping & Production Delivery
- Partner directly with engineering teams to understand workflows, pain points, and opportunities through hands-on discovery.
- Rapidly prototype and validate new AI capabilities with real users, then take successful prototypes into secure, observable, maintainable production systems.
- Own the full lifecycle: implementation, testing, deployment, monitoring, and iteration.
Technical Leadership
- Provide hands-on technical leadership through architecture discussions, code reviews, and troubleshooting of agentic systems.
- Mentor engineers on agentic design patterns, prompt engineering, and agent-native development practices.
- Communicate tradeoffs, risks, and results clearly to both technical and non-technical stakeholders.
- Contribute to engineering standards, reusable patterns, and documentation that help other teams build effectively with agentic development tools.
Requirements
- 6+ years of professional software engineering experience, including significant hands-on work building and operating AI/LLM-powered or agentic applications.
- Strong programming skills (Java, Python, Go, Rust, or C++) and solid engineering fundamentals — API design, testing, debugging, code review, maintainable code.
- Practical, production-grade experience with agentic SDKs/harnesses, MCP, and LLMs — tool use, orchestration, RAG, context management, structured output, and evaluation.
- Experience designing MCP tool/resource interfaces and reasoning about tool selection, error handling, and reliability in multi-agent systems.
- Demonstrated experience integrating AI into CI/CD and developer workflows.
- Ability to work in ambiguous problem spaces, evaluate tradeoffs, and make pragmatic engineering decisions.
- Strong written and verbal communication skills, with experience mentoring and leading through influence.
Preferred Qualifications
- Demonstrated expertise across agentic architecture, MCP integration, Codex/Claude Code configuration, prompt engineering, and context management.
- Experience building multi-agent research or customer support systems, or structured data extraction pipelines.
- Experience with AWS, Docker, Kubernetes, Terraform, and GitOps in support of AI/agentic infrastructure.
- Familiarity with vector databases, embeddings, and AI evaluation frameworks.
- Contributions to open-source projects involving AI, agentic systems, or developer tooling.
- Strong systems thinking — understands how models, agents, tools, context, APIs, data, and infrastructure fit together as production systems, and can reason about dependencies and tradeoffs across the stack.
- A track record of adapting quickly to new AI tools, models, and frameworks as the space evolves.
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Salary Context
This $177K-$265K range is above the median for AI Software Engineer roles in our dataset (median: $193K across 172 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Sony Interactive Entertainment, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. Disclosed range: $177K to $265K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Sony Interactive Entertainment AI Hiring
Sony Interactive Entertainment has 5 open AI roles right now. They're hiring across AI Software Engineer, AI Safety, AI/ML Engineer, Data Scientist. Positions span San Diego, CA, US, San Mateo, CA, US, London, England, UK. Compensation range: $199K - $265K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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