Full Stack Engineer (Delivery Toolkit)

Atlanta, Austin, Chicago, Dallas, Houston Description & Requirements

WHO YOU’LL WORK WITH

As the premier consulting partner for the private equity industry, Bain's PEG boasts a global practice that is over three times larger than any competitor. Our network of over 1,000 professionals supports private equity and institutional investor clients through every stage of the investment life cycle, from deal generation and due diligence to portfolio value creation and exit planning. Bain & Company is developing a suite of cutting‑edge data and software solutions designed to revolutionize how the private equity industry uses data for investment insights and decision‑making. The PEG Innovation team's mission is to create analytical solutions for Bain clients, teams, and the broader institutional investor space using proprietary software and data products. This includes the development, commercialization, and daily management of Bain's proprietary datasets, data, and software businesses.

WHERE YOU’LL FIT WITHIN THE TEAM

Full‑Stack Engineers in Product Engineering build and maintain the end‑user products that PE analysts, associates, and partners use daily, including Deal Screening, Due Diligence workflows, Portfolio Monitoring, Report Builder, and more. You contribute across the full product surface: Svelte/Sveltekit frontend, concrete API contract surface, and product‑specific Node.js/FastAPI services, with guidance from senior engineers. You are expected to deliver production‑quality code, write tests for the workflows you build, and partner with Product and Design to translate requirements into reliable user experiences. You collaborate with Cross‑team Engineering for shared services (Auth/RBAC, Audit, Notifications, File Service) and work with the Agent / AI as needed to integrate intelligent features safely and correctly. For this role we weight foundational engineering capability above AI engineering experience. The expected tenure is multi‑year, and we believe AI tooling and techniques will continue to shift quickly, while strong programming fundamentals, system design judgement, and the ability to write maintainable, scalable code remain durable. Inside Core Product we treat AI as a co‑pilot and tool, not an autopilot and replacement: every AI generated change is expected to be reviewed and validated by the engineer who commits it. Practical AWS and DevOps experience is a strong differentiator, given how heavily our products rely on AWS services, deployment pipelines, and cloud infrastructure day to day.

WHAT YOU'LL DO

Product Feature Delivery Across UI and Services (80%) Implement product UI features in Svelte and TypeScript by following established component patterns and the shared design system. Build and maintain RESTful API functionality under existing schemas and patterns: implement routes, schemas, and client queries/mutations with guidance. Implement and maintain product‑specific Node.js/FastAPI endpoints using Zod/Pydantic v2 and PostgreSQL/SQLAlchemy patterns; follow established code conventions and PR standards. Write and update migrations for product schemas using safe, backwards‑compatible patterns (expand/contract) with review support. Integrate with platform shared services correctly (Auth/RBAC, Audit, Notifications, File Service); raise contract issues early and coordinate changes through the team. Write unit and integration tests for delivered features (Vitest/RTL for frontend, Jest/pytest for backend); contribute to E2E tests (Playwright) for owned workflows. Add basic observability for owned changes: follow established logging patterns, emit standard metrics where applicable, and update dashboards/runbooks for impacted workflows. Contribute to containerised delivery for owned services (Docker) under guidance. Support releases for owned work: verify changes in staging, participate in incident triage when needed, and follow runbooks/escalation paths. Other (20%) Participate fully in team ceremonies (refinement, planning, standup, review, retro); ask clarifying questions early and communicate blockers clearly. Participate in code reviews as both author and reviewer; incorporate feedback and improve code quality over time. Contribute to shared product infrastructure: small enhancements to the design system and API client libraries (OpenAPI / type generation) under guidance. Use AI coding assistants to accelerate scaffolding, refactors, and first‑pass tests; validate all generated code carefully before committing. Contribute to documentation for delivered features (release notes, runbook updates, and lightweight technical notes) as part of the Definition of Done.

ABOUT YOU

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience). 2+ years of experience building web applications or backend services in a production or near‑production environment. Demonstrated experience implementing features in TypeScript across Node.js services and frontend frameworks and writing tests for shipped work. Experience contributing to backend APIs in Node.js and FastAPI and working with relational databases, including basic schema evolution/migrations. Comfortable collaborating with Product and Design to translate requirements into working software and iterating based on feedback. Practical, hands‑on AWS experience is a strong differentiator for this role. Production exposure to core AWS services (e.g. S3, RDS, Lambda, ECS, CloudWatch, IAM, API Gateway, SQS or SNS) and deployment pipelines built on top of AWS is highly valued. Demonstrated strength in foundational engineering: programming fundamentals, clean coding principles, system design judgement, and the ability to write maintainable, scalable code. We weight this above breadth or depth of AI engineering experience. Svlete or React and TypeScript fundamentals: hooks, component composition, state management basics, and performance‑aware UI development. Frontend testing: Vitest basics; able to write reliable unit/integration tests and debug failures. Backend fundamentals in Node.js/Python: API endpoints, validation models, and basic async/service patterns under established conventions. SQL fundamentals: able to write and debug queries and work with Postgres‑backed schemas under established patterns. Migration basics: understands safe migration practices and the expand/contract approach for backwards‑compatible schema changes. Docker basics: comfortable building/running containers locally and following non‑root image conventions where required. CI/CD familiarity: comfortable reading GitHub Actions workflow output and fixing common test/lint issues in PRs. AWS services in practice: hands on use of core services (S3, RDS or Aurora, Lambda, ECS, CloudWatch, IAM, API Gateway, SQS or EventBridge) for product work, including reading IAM policies, triaging CloudWatch logs and metrics, and reasoning about cost and scaling implications of service choices. Deployment pipelines on AWS: comfortable extending CI/CD workflows that build, test, and deploy services into AWS environments; able to debug pipeline failures end to end (build, image push to ECR, deploy step, post deploy health checks). Infrastructure as code familiarity: working knowledge of Terraform or CloudFormation/CDK for AWS resources; able to read existing modules, make scoped changes, and review IaC PRs with a security and cost lens. Generative AI and Agentic Systems Treats AI coding assistants (Cursor, GitHub Copilot, or equivalent) as a co‑pilot, not an autopilot. Uses them to scaffold, refactor, and draft first pass tests, but applies strong critical thinking and engineering judgement to read, understand, and revise every line of generated code before committing. Does not ship AI generated code that the engineer cannot fully explain. Uses LLMs to draft first‑pass documentation and test cases; validates correctness and fills gaps manually. Understands at a high level how AI features appear in product UIs (e.g., streaming responses, structured outputs) and follows established patterns for safe integration. General Builds for users: optimises for analyst workflows and clarity, not just technical elegance. Delivers production‑quality work: tests, basic observability, and documentation are part of the Definition of Done. Raise concerns early when requirements, contracts, or data models are unclear; seeks help rather than getting stuck. Uses AI tooling to move faster on routine work, but never as a substitute for understanding the change. Reads, reasons about, and revises every AI generated diff; rejects suggestions that the engineer cannot fully justify on their own merits. This role follows a hybrid model, requiring in‑office presence at least 1 day per week

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 be included in job postings for open roles. The estimated annualized compensation for this role is as follows: In Atlanta, the good‑faith, reasonable annualized full‑time salary range for this role is between $92,750 - $101,250 In Texas, the good‑faith, reasonable annualized full‑time salary range for this role is between $97,375 - $106,250 In Chicago, the good‑faith, reasonable annualized full‑time salary range for this role is between $102,250 - $111,500 Placement within these ranges will vary based on factors such as experience, education, training, and skill level. Compensation also includes a discretionary annual performance bonus, 401(k) plan with employer contribution, and Bain’s best‑in‑class benefits—including full premium coverage for medical, dental, and vision, generous paid time off, and more. 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 #J-18808-Ljbffr Bain & Company