Director, Full stack AI Engineer

Bain & Company • Boston, MA

8d • $196,000 - $245,750

About The Position

The Director, Full stack AI Engineer will build and operate the product interfaces and backend services for Bain’s Growth AI Performance System, an integrated suite of agentic decisioning tools for large organizations. This platform-wide role spans the Agentic Core and Interface team and supports product modules focused on marketing ROI, brand, and pricing strategy. The role owns the full stack, from APIs serving analytical and agentic outputs to React interfaces used by consultants, specialists, and senior client stakeholders in live commercial engagements.

The Director will partner with design, AI engineering, data engineering, product, and consulting teams to deliver fast, reliable, data-dense interfaces and integrate agentic and LLM-powered capabilities. Responsibilities include establishing the product’s design-system implementation and engineering standards, maintaining production performance and security, and translating client feedback into product improvements. The position also manages a small team of mid- to senior-level engineers, including day-to-day coaching, performance reviews, development planning, recruiting, and onboarding.

The role is part of a standing product team operating like a startup within Bain, with early-stage ownership and influence over architecture and product direction, supported by Bain’s scale and client relationships. The work includes real-time decision engines, cloud-native infrastructure, and enterprise data challenges, with production users relying on the resulting software.

Requirements

• Deep proficiency in React and TypeScript for complex frontend development, including component architecture, state management, performance optimization, and maintainable code conventions.
• Strong server-side development skills and experience building reliable, versioned, performant APIs and backend services for analytical and AI-generated outputs at production scale.
• Experience building data-dense analytical interfaces, including chart-heavy dashboards, real-time scenario tools, multi-variable comparisons, and allocation displays using modern visualization libraries.
• Experience integrating LLM and agentic AI capabilities into user-facing product features, including presentation of AI outputs, streaming responses, and confidence indicators.
• Strong engineering fundamentals, including clean and testable code, component-library development and governance, CI/CD ownership, automated testing, debugging, and performance profiling.
• Experience deploying and operating full-stack applications on Azure or AWS; proficiency with containerization and understanding of cloud-native deployment and monitoring.
• Understanding of authentication, authorization, and secure data handling, with experience applying DevSecOps principles in an enterprise full-stack application.
• Familiarity with design-system implementation, including translating design tokens, component documentation, and interaction guidelines into consistent engineering conventions.
• Active use of AI-assisted coding tools such as Cursor, Claude Code, or equivalent.
• At least 10 years of full-stack software engineering experience, with significant hands-on work across frontend and backend.
• Direct experience managing engineers, including performance reviews, professional development planning, and day-to-day people management.
• Track record of building and shipping production applications with data-dense analytical interfaces used by professionals.
• Experience leading engineering implementation of a design system or component library across a multi-feature product.
• Experience mentoring engineers and setting team engineering standards.
• Experience working in agile, cross-functional product teams, with strong troubleshooting and production issue-resolution skills.
• Associate’s or bachelor’s degree in computer science, engineering, mathematics, or a related technical field, or an equivalent combination of education, training, and experience.

Nice To Haves

• Experience in client-facing or consulting-adjacent environments where interface decisions affect how professional users trust and act on information.

Responsibilities

• Build and ship end-to-end product features using React and TypeScript, including API integration, deployment, and ongoing maintenance.
• Own feature areas and interface workstreams across channel allocation dashboards, scenario-planning tools, marketing ROI outputs, brand analytics, and pricing strategy displays.
• Build data-dense, chart-heavy interfaces, including time-series views, waterfall charts, allocation comparisons, scenario tools, and real-time output displays.
• Implement human-agent interaction components with the AI Engineering team, clearly presenting recommendations, confidence indicators, scenario outputs, and uncertainty.
• Build and maintain reliable, versioned, performant backend APIs serving domain-model outputs, agentic workflow results, and platform data.
• Lead implementation and maintenance of the Growth AI Performance System design system and component libraries; establish consistent frontend engineering conventions.
• Write clean, testable, maintainable code and implement CI/CD pipelines, automated testing, and deployment workflows.
• Own interface-layer performance and reliability; monitor performance, API latency, and errors, and resolve issues affecting live client deployments.
• Apply DevSecOps principles, including authentication, authorization, secure client-data handling, and relevant privacy compliance.
• Mentor engineers, including the Data Engineer; set engineering standards, provide code-review feedback, and support progressively greater ownership.
• Manage a small team of mid- to senior-level engineers, including weekly check-ins, work unblocking, and escalation for technical and delivery issues.
• Manage direct reports’ performance cycles, including reviews, goals, feedback, and professional development plans.
• Build team fluency in AI/ML and AI-assisted development practices; identify skill gaps and guide professional growth.
• Lead team recruiting, define hiring needs, participate in interviews, and oversee onboarding.
• Foster team job satisfaction and growth while managing conflict and cross-team dependencies to keep delivery on track.
• Engage with consulting teams around live client deployments, identify interface friction or performance and credibility issues, and prioritize engineering improvements alongside the roadmap.
• Explain interface architecture, engineering tradeoffs, and technical decisions to senior stakeholders; contribute to platform demonstrations.
• Coordinate across design, AI engineering, and product disciplines by translating specifications into requirements, surfacing integration constraints, and communicating delivery status and risks.
• Stay current with frontend technologies, AI-powered interface patterns, and data-visualization approaches, and propose relevant engineering improvements.

Benefits

• Annual discretionary performance bonus and potential eligibility for other discretionary compensation.
• 4.5% 401(k) company contribution, increasing after three years of service and fully vested upon start date.
• Bain pays 100% of individual employee premiums for medical, dental, and vision programs.
• Generous paid time off, including parental leave, sick leave, and paid holidays.
• Paid life and long-term disability insurance.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Associate degree