Senior Software Engineer

Drive the future of Agentic AI at Pearson as part of the AgentOps Engineering team. Inspire innovation. Empower learning. Pearson, the world’s leading learning company, is hiring a Senior Software Engineer to play a key role on our AgentOps Engineering team. Why This Role Matters Are you passionate about building AI agents that reason, plan, route work, and run reliably in production—not just prototypes? Do you want to shape how an enterprise builds, operates, and governs digital workers at scale? Join our AgentOps Engineering team and help build the core platform capabilities that power agent crews running across the business. This is a hands‑on senior engineering role focused on building . You’ll ship the write‑path features that let agents take real actions, design the orchestration and routing patterns that direct work to the right agent, and engineer enhancements to the platform itself—working inside it, not just on top of it. Through this, you’ll help teams across Pearson put dependable AI agents to work, and help people realize the lives they imagine through learning. As a key member of the AgentOps Engineering team and Pearson, you will be expected to embody, and role model our leadership dimensions: Live Our Purpose: You connect your engineering work to Pearson’s mission and make decisions that reflect a clear understanding of our strategy. Simplify the Complexity: You navigate ambiguity in a fast‑changing field and distil complex agentic systems into clear, reliable solutions. Carry Our Culture: You collaborate generously, mentor through design and code reviews, and contribute to an inclusive, high‑performing team. Deliver Results: You set a high‑quality bar, get the details right, and own outcomes that matter to learners and stakeholders. What You’ll Do Build write‑path features Ship the features that let agents take real, governed actions—wrapping enterprise APIs, validators, and data sources so agents can write, not just read. Design safe write semantics: idempotency, confirmation and human‑in‑the‑loop gates, structured outputs, and audit‑ready action logging. Build multi‑agent and digital‑worker orchestration patterns that let specialized agents delegate, collaborate, and complete multi‑step goals. Build stateful, cyclic workflows using modern agent orchestration frameworks—enabling reflection, recovery, and adaptive execution beyond linear chains. Build the routing layer that directs requests to the right agent or crew—intent classification, capability‑based dispatch, fallback, and escalation paths. Create reusable components for retries, degraded modes, and human handoff; tune agent roles, goals, and prompts using fixtures and golden sets. Enhance the platform Work hands‑on with the agentic platform—creating, versioning, invoking, and debugging crews, tasks, and graphs through platform APIs—and contribute enhancements back where new patterns are needed. Design long‑running, resumable workflows (checkpointing, persistence, context restoration) and resilience patterns for non‑deterministic AI. Ship with AI, at quality Work primarily through AI‑pair‑programming as your default mode—researching, scaffolding, implementing, reviewing, and shipping at high velocity while holding quality through TDD and rigorous verification. Raise the bar Drive reusable engineering standards, shared libraries, and reference patterns; mentor engineers through design and code reviews; and share the prompts, skills, and workflows that multiply everyone’s output. Who You Are A hands‑on senior engineer who builds production‑grade agentic systems, not demos. An independent owner who takes complex workstreams from ambiguity to reliable, shipped software. A collaborator who influences through standards and mentoring, without needing authority. Someone with strong taste and trade‑off judgment across quality, latency, cost, resilience, and maintainability. What You’ll Bring You build LLM‑powered systems, agents, or digital workers that run in production. Strong Python and backend/platform engineering—async services, typed code, and clean architecture. You work fluently with agent orchestration frameworks and can design, build, and orchestrate reliable agent tools—contracts, error handling, tool chaining. You’ve built routing, dispatch, or workflow‑control logic that directs work across components or services. You use AI‑pair‑programming as a primary delivery mode without sacrificing quality. Strong prompt engineering for structured outputs, nested schemas, and multi‑agent coordination. You read, edit, and contribute to a real platform codebase—APIs, runtime, storage—not just an SDK. Solid APIs, distributed systems, and cloud‑native engineering, with production‑reliability instincts. Experience evaluating agents—task success, groundedness, tool‑use accuracy, schema conformance, and regression against golden fixtures. Experience with tool/context interoperability protocols (such as MCP). Experience with a major cloud platform (AWS preferred), containerization, and CI/CD; familiarity with state stores for orchestration and persistence. AI observability and evaluation tooling for LLM systems. RAG and memory patterns: vector databases, hybrid retrieval, re‑ranking, and grounding. Secure execution, sandboxing, and prompt‑injection mitigation. What You’ll Gain A front‑row seat building enterprise agentic AI infrastructure that teams across Pearson rely on. Real ownership of orchestration, routing, and platform patterns others adopt. A collaborative, inclusive, and innovation‑driven culture. Access to cutting‑edge tools, platforms, and thought leadership. Why Pearson? At Pearson, we don’t just build careers—we accelerate them. Known for our strong culture of internal mobility and leadership development, we offer a clear path to broader technical and leadership roles. We believe great work deserves great rewards. That’s why we offer some of the most competitive benefits in the industry—designed to support the diverse needs of our people and their families. Explore our Benefits. At Pearson, we’re reimagining learning through technology. If you’re an engineer who thrives in complexity, builds with craft, and is excited to put AI agents to work at scale—we’d love to hear from you. Compensation at Pearson is influenced by factors including skill set, experience, and location. The full‑time salary range for this role is $90,000 – $135,000. This position is eligible to participate in an annual incentive program. Information on benefits can be found here. Applications will be accepted through 5th August 2026. This window may be extended depending on business needs. Who we are: At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson. Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing View email address on click.appcast.io. #J-18808-Ljbffr Pearson