СШАSenior Software Engineer - AI & Agentic Architecture
1 нед. назад
177.3k–265.9k USD / годСШАSenior
sdkapiagentic systemssoftware engineering
Senior individual-contributor role designing and building AI agentic systems and developer tooling for PlayStation.
О компании
- isn’t just the Best Place to Play — it’s also the Best Place to Work. (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.
Требования
- 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.
Будет плюсом
- 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.
Условия
- At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more.
- The estimated base pay range for this role is listed below.
- $177,300 — $265,900 USD
- Please note, 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.
Другое
- 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.
- 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.
- 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.
- 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.
- 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.