Director, Full stack AI Engineer

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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

Technical

• Deep proficiency in React and TypeScript for complex frontend development; strong command of component architecture, state management, performance optimization, and the engineering conventions that make large frontend codebases maintainable
• Strong server-side development proficiency; experience building reliable, versioned, performant APIs and backend services that serve analytical and AI-generated outputs to frontend clients at production scale
• Experience building data-dense analytical interfaces: chart-heavy dashboards, real-time scenario tools, multi-variable comparison views, and allocation displays using modern visualization libraries
• Experience integrating LLM and agentic AI capabilities into user-facing product features; understanding of how to surface AI-generated outputs, streaming responses, and confidence indicators in interfaces that professional users depend on
• Strong engineering fundamentals: clean, testable code; component library development and governance; CI/CD pipeline ownership; automated testing; and production-grade debugging and performance profiling
• Experience deploying and operating full-stack applications on Azure or AWS; proficiency with containerization and understanding of how frontend and backend services are deployed and monitored in a cloud-native environment
• Solid understanding of authentication, authorization, and secure data handling; experience applying DevSecOps principles across a full-stack application in an enterprise context
• Familiarity with design system implementation: able to translate design token specifications, component documentation, and interaction guidelines into engineering conventions that a team can build from consistently
• Active use of AI-assisted coding tools (Cursor, Claude Code, or equivalent) to accelerate development, prototype faster, and raise the engineering productivity floor of the team

Experience

• 10 or more years in full-stack software engineering roles with significant hands-on building responsibilities across both frontend and backend
• Direct experience managing a team of engineers: running performance reviews, professional development planning, and day-to-day people management, in addition to technical leadership
• Track record of building and shipping production applications with data-dense analytical interfaces that real professional users depend on
• Experience leading the engineering implementation of a design system or component library across a multi-feature product
• Experience mentoring engineers and setting engineering standards within a team
• Experience in client-facing or consulting-adjacent environments where interface decisions have direct consequences for how professional users trust and act on what they see is a strong advantage
• Experience working in agile, cross-functional product teams; strong troubleshooting and production issue resolution skills

Education

Associate’s degree / Bachelor’s degree in computer science, engineering, mathematics, or a related technical field; or an equivalent combination of education, training, and experience.

U.S. Compensation Information

Compensation for this role includes base salary, annual discretionary performance bonus, 401(k) plan with an annual employer contribution based on years of service and Bain’s best in class benefits package (details listed below).

Some local governments in the United States require a good-faith, reasonable salary range to be included in job postings for open roles. The estimated annualized compensation for this role is as follows:

• In Illinois, the good-faith, reasonable annualized full-time salary range for this role is between $196,000-235,250; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level
• In Massachusetts, the good-faith, reasonable annualized full-time salary range for this role is between $204,750-$245,750; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level
• Annual discretionary performance bonus
• This role may also be eligible for other elements of discretionary compensation
• 4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date

Bain & Company’s comprehensive benefits and wellness program is designed to help employees achieve personal independence, protection and stability in the areas most important to you and your family.

• Bain pays 100% individual employee premiums for medical, dental and vision programs, offering one of the most comprehensive medical plans for employees without impacting your paycheck
• Generous paid time off, including parental leave, sick leave and paid holidays
• Fully vested 401(k) company contribution
• Paid Life and Long-Term Disability insurance

For all other locations, the good-faith, reasonable annualized full-time salary range for this role is commensurate with competitive geographic market rates for this role and will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.