🇪🇺 United Kingdom
Permanent
23 Oct 2026
🏢 Bain & Company, Inc.
📍 Not Specified
Boston, Chicago, London, Sao Paulo, Warsaw Description & Requirements What Makes Us a Great Place to Work We are proud to be consistently recognized as one of the world's best places to work. We are currently the top ranked consulting firm on Glassdoor's Best Places to Work list and have earned the overall spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don't happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally. Who You'll Work With You will be part of a team building Bain's integrated suite of agentic decisioning tools that gives large organizations always on intelligence across their most important growth decisions. The role sits at an intersection few organizations can offer: the analytical depth and client access of a top tier consultancy, the technical ambition of a product company, and engineering work at the frontier of applied AI. You will work inside Bain's standing product team, building software that helps the world's largest companies answer the questions that drive their business: where to invest, where to focus, and how to win. The impact of what you build is direct and immediate, and the platform compounds in value with every release. The platform has two layers working together: an agentic core and a set of decision modules, each solving a distinct commercial problem. The build lifecycle is connected to the real world: as case teams work alongside clients across industries and geographies, that feedback flows straight back to engineering and into the product. Every client engagement makes the platform smarter, broader, and more resilient. This is a startup inside an established company. You get genuine early stage ownership and real influence over architecture and product direction, backed by Bain's global scale, client relationships, and leadership commitment; the pace of a startup with the runway of a global firm. We are looking for engineers who see how to make a product better and bring that instinct to every sprint without being asked, and who are comfortable with problems that do not have a known answer. The work involves real time decision engines, cloud native infrastructure, and data problems with no off the shelf answer. Experience with agentic systems matters: tool and context protocols such as MCP, evaluation harnesses, memory design, and entity resolution across messy enterprise data. This is applied AI in production, at scale, with real users depending on what you build. The field is moving quickly and the team is built to move with it, so the willingness to keep learning counts for as much as what you already know. Where You'll Fit Within the Team The Full-stack Engineer owns the build and operation of the product interfaces and backend services that surface Growth AI Performance System capabilities to users across the full suite: the dashboards, workflow tools, scenario planning interfaces, and output views that Expert Consultants, specialists, and senior client stakeholders use in live commercial engagements. This is a platform-wide role within the Agentic Core and Interface team: you are building for all three product modules, not for one. You will work closely with the Design Lead and Designer on the front end, with AI Engineers on the integration of agentic and LLM powered capabilities into the interface layer, and with the Data Engineer on the data access and API layer that feeds what users see. You are responsible for the quality, reliability, and performance of the full stack: from the API surface that serves domain model outputs through to the React components that render them for users. This is also a people leadership role. You will be the line manager for a small team of mid to senior level engineers within the Agentic Core and Interface team, owning their day to day work, performance, and growth: running weekly check ins, serving as the point of escalation, writing mid year and annual performance reviews, and setting professional development plans that build the team's fluency with AI assisted engineering practices. You will work across the platform and product modules focused on marketing ROI, brand, and pricing strategy, building interfaces that make complex analytical outputs navigable and credible for professional users who need to act on them quickly. The users of this product are sophisticated; the interfaces need to be fast, dense, and unambiguous. This role has direct client proximity. You will engage with consulting teams to understand how the interfaces are being used in live engagements, where performance or reliability is creating problems, and what engineering changes are needed. What You'll Do Building and shipping product interfaces Build and ship end to end product features across the Growth AI Performance System frontend: React and TypeScript component development, API integration, and the full feature lifecycle from design handoff through to production deployment and ongoing maintenance Own specific feature areas and interface workstreams across the suite: channel allocation dashboards, scenario planning and what if tools, marketing ROI output views, brand analytics interfaces, and pricing strategy displays, designed for expert users who need to navigate dense analytical content quickly Build data dense, chart heavy interfaces using modern visualization libraries; implement time series views, waterfall charts, allocation comparisons, multi variable scenario tools, and real time output displays that update as model inputs change Implement human agent interaction components in collaboration with the AI Engineering team: how agentic recommendations, confidence indicators, scenario outputs, and uncertainty are surfaced to users in interfaces that are clear, credible, and professionally appropriate Build and maintain the backend API layer that serves domain model outputs, agentic workflow results, and platform data to the frontend; design APIs that are reliable, versioned, and performant at production scale Engineering quality and platform standards Lead the engineering implementation of the Growth AI Performance System design system: build component libraries that faithfully implement design specifications, maintain them as the design system evolves, and establish engineering conventions that make the frontend codebase consistent and maintainable across the full suite Write clean, testable, maintainable code across the full software development lifecycle; implement CI/CD pipelines, automated testing, and deployment workflows that support rapid iteration without sacrificing production stability Own performance and reliability for the interface layer: monitor frontend performance, API latency, and error rates; diagnose and resolve issues that affect the user experience in live client deployments Apply DevSecOps principles across the full stack: authentication and authorization, secure data handling for client commercial data, and compliance with privacy obligations relevant to the platform's enterprise client context Mentor engineers on the team, including the Data Engineer; set engineering standards, provide structured code review feedback, and create opportunities for team members to take on progressively more ownership People management and team leadership Manage a small team of mid to senior level engineers day to day: run weekly check ins, unblock work, and serve as the point of escalation for technical and delivery issues Own the full performance cycle for direct reports: write and deliver mid year and annual reviews, set goals, provide constructive feedback, and build individual professional development plans Build AI/ML fluency across the team: set expectations for AI assisted development practices, identify skill gaps, and guide reports' growth into AI augmented engineering roles Lead recruiting for the team: define hiring needs, participate in interviews, and own onboarding so new engineers reach full productivity quickly Create and foster a high job satisfaction environment that supports continued growth and advancement for the team, while managing conflict and cross team dependencies to keep delivery on track Collaboration and communication Engage with consulting teams during and after live client deployments to understand where the interface layer is creating friction, performance problems, or credibility issues; translate that feedback into engineering improvements and prioritize them alongside the product roadmap Present interface architecture, engineering tradeoffs, and technical decisions to senior stakeholders in clear, non technical terms; contribute to stakeholder sessions where the platform's interfaces are demonstrated and explained Communicate clearly across design, AI engineering, and product disciplines; translate design specifications into engineering requirements, surface integration constraints to the design team early, and keep product management informed of delivery status and technical risks Drive innovation in interface engineering: stay current with emerging frontend technologies, AI powered interface patterns, and data visualization approaches; bring relevant learnings back to the team and propose improvements to the engineering approach About You . click apply for full job details