Platform Engineer

About the Company

We are proud to be consistently recognized as one of the world’s best places to work, currently ranked as the top consulting firm on Glassdoor’s Best Places to Work list with the #1 overall spot earned a record seven times. Extraordinary teams are central to our business strategy, intentionally built to bring together diverse backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire exceptional talent and create an environment where every individual can thrive professionally and personally.

As the premier consulting partner for the private equity industry, Bain's Private Equity Group (PEG) boasts a global practice 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 cutting-edge data and software solutions 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, including development, commercialization, and daily management of Bain’s proprietary datasets and software businesses.

About the Team

Platform Engineers build and maintain the shared backend services that power the Bain Diligence Platform (BDP). These include enterprise SSO, session management, audit, case and case-provenance APIs, document and file access (Microsoft Graph / SharePoint and Azure Blob Storage), search with source citations, and the API gateway. You will contribute to services across the full delivery lifecycle—design, build, test, deploy, monitor, and operate—with guidance from senior engineers.

Responsibilities

• Core Platform Service Development, Deployment, and Operations (80%)
  • Implement backend features and service endpoints in existing platform services under the guidance of senior engineers.
  • Build and maintain REST APIs in FastAPI using clear contracts, input validation, and consistent error handling.
  • Write and update Postgres schemas and Alembic migrations using safe patterns (including backwards-compatible changes) with review support.
  • Use Redis for standard platform patterns such as caching, session storage, and rate limiting under established conventions.
  • Implement event-driven integration where asynchronous behavior adds clear value (e.g., change feeds and domain events), following existing schema and envelope conventions.
  • Add and maintain service instrumentation: structured logs, OpenTelemetry-style spans, and Datadog metrics and APM traces according to platform standards.
  • Update and maintain Helm chart values and Kubernetes manifests for services deployed to Azure Kubernetes Service (AKS); ensure probes, resource requests/limits, and environment configuration are correct, and support blue/green candidate/promote deployments.
  • Contribute to Terraform infrastructure-as-code for Azure, deployed through env0 / Terraform Cloud across dev, UAT, and prod environments, with review support.
  • Work within GitHub Actions pipelines: pull-request test suites, branch-to-environment promotion (main → Dev, release/X.Y → UAT/Prod), image publishing to Cloudsmith, and blue/green candidate/promote deploys with approval gates.
  • Triage and resolve routine production issues for owned services; participate in on-call rotation with support and follow established runbooks.
  • Write and update runbooks and service documentation for changes you ship, ensuring operational steps remain accurate.
• Other (20%)
  • Participate in code reviews as both author and reviewer; incorporate feedback and apply engineering standards consistently.
  • Use AI coding assistants to accelerate boilerplate creation (routers, schemas, tests, docs); review all generated code and align it with platform conventions before committing.
  • Use LLMs to draft first-pass documentation (runbook updates, service notes, API docs); validate and refine outputs before publishing.
  • Collaborate with Security and Infrastructure on implementation tasks (e.g., Azure Key Vault secret consumption, Entra ID app registrations, network-security-group / private-endpoint constraints, least-privilege configuration, and Wiz security-scan findings) under guidance.
  • Contribute to quality improvements (test coverage, refactors, observability, and reliability fixes) as part of regular delivery work.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
• 2+ years of experience building backend services, APIs, or platform components in a production or near-production environment.
• Demonstrated experience building and maintaining backend services or APIs with an emphasis on reliability and correctness.
• Experience contributing to REST APIs and working with relational databases (Postgres preferred), including basic schema evolution and migration workflows.
• Exposure to containerized development and deployment practices (Docker) and familiarity with operating services in Kubernetes environments (Azure / AKS in practice).
• Exposure to authentication and authorization concepts (JWT, RBAC, OIDC/SAML — Entra ID / Azure AD in practice) and interest in building secure-by-default services.
• Demonstrated ability to learn from feedback, collaborate effectively, and deliver production-ready work within established engineering standards.

Skills

• Backend / Platform Engineering
  • Proficient Python development skills; able to build FastAPI services using Pydantic, write tests with pytest, and follow linting/type-checking standards (Ruff, mypy), and manage environments and dependencies with uv.
  • Working knowledge of Postgres fundamentals: schema design basics, indexing concepts, and safe migration practices with Alembic.
  • Working knowledge of Redis patterns for caching and session storage; understands basic failure modes and operational considerations.
  • Familiarity with event-driven integration patterns applied where asynchronous behavior adds value (change feeds / domain events, consumers, retries, idempotency); able to implement producers/consumers within established conventions.
  • Docker proficiency for local development and building container images; understands non-root execution and basic image hygiene.
  • Kubernetes fundamentals: understands deployments/services, pod lifecycle basics, and how health checks and resource limits affect service behavior; able to work with Helm values and charts on AKS, including blue/green deployments.
  • Observability fundamentals: structured logging, tracing concepts, and emitting metrics and APM traces via Datadog for service health; awareness of MLflow for evaluating AI features.
  • Security fundamentals: understands least-privilege access, secret-handling basics, and common authN/authZ concepts; follows established patterns for JWT and RBAC integration, Entra ID, and Azure Key Vault.
  • Familiarity with infrastructure-as-code (Terraform) and CI/CD via GitHub Actions; understands environment promotion, container registries (Cloudsmith), Helm chart versioning, and blue/green deployments on AKS.
• Generative AI and Agentic Systems
  • Uses AI coding assistants (Cursor, GitHub Copilot, or equivalent) to accelerate development tasks (boilerplate, refactors, basic tests); reviews all outputs critically before committing.
  • Uses LLMs to draft first-pass unit tests and documentation; validates correctness, adds missing edge cases, and ensures alignment with platform standards.
  • Understands how core platform services (SSO/JWT authentication, RBAC, audit, and case provenance) underpin agentic systems, and why access control, auditability, and provenance matter for AI interactions—including the platform’s “skills orchestrate, agents execute” model.
  • Familiarity with the LLM-application patterns used on the platform: an LLM gateway (Portkey) for model access and routing, structured / tool-constrained outputs with schema validation and automatic repair, and retrieval-grounded answers with citations back to source.
  • Exposure to eval-driven development for AI features—building evaluation cases and using MLflow to measure quality, regressions, and repair uplift before promoting changes.
• General
  • Treats every service change as production-impacting: writes tests, adds observability where needed, and updates documentation and runbooks.
  • Raises risks early (unclear requirements, security concerns, migration risk, operational impact) and seeks help appropriately.
  • Uses AI tooling to move faster, but applies judgment and careful review to all generated code and documentation before it enters the codebase.
  • Maintains a strong ownership mindset for assigned work: follows through from implementation to deployment support and post-release verification.
  • Favors the simplest solution that meets the need—introducing new components, services, or infrastructure only when a concrete requirement justifies it, and keeping services secure-by-default, observable, versioned, and backward-compatible.

Schedule

This role follows a hybrid model, requiring in-office presence at least 1 day per week.

Pay

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 a comprehensive benefits package. The estimated annualized compensation for this role is as follows:

• Atlanta: $70,375 - $76,750
• Texas: $73,750 - $80,500
• Chicago: $77,500 - $84,500

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 other elements of discretionary compensation.

Benefits

• 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.
• Fully vested 4.5% 401(k) company contribution, which increases after 3 years of service.
• Paid Life and Long-Term Disability insurance.