Principal Software Engineer

Aderant•Atlanta, GA

14d

About The Position

Aderant is a global industry leading software company providing comprehensive business management solutions for law firms and other professional services organizations with a mission to help them run a better business. We are motivated by a collective desire to drive the legal industry to the forefront of innovation. With over 2,500 clients around the world, including 95 of the top AmLaw 100 firms, we are changing the outside perception of the legal sphere; where there was once resistance to modernization, we are creating a culture that embraces new ideas and technology. At Aderant, the “A” is more than just a letter. It is a representation of how we fulfill our foundational purpose, serving our clients. It embodies our core values and reminds us that to achieve success, every day must start with the “A”. We bring the “A” to life by fostering a culture of innovation, collaboration, and personal growth. We encourage our diverse teams to bring their whole selves to work – ideas, experience, and passion – to drive our mission forward. Our people are our strength. We are seeking a Principal Software Engineer to help build Aderant Talent, the next generation of vi by Aderant. Our talent management suite is used by the world's leading law firms to recruit, evaluate, develop, and allocate their people. This is a greenfield platform on AWS, with a backend of TypeScript/Node and Go services over MongoDB, behind a React front end. You will set service boundaries, document models, API contracts, and engineering standards while they are still cheap to change. Two things make the work hard. Aderant Talent holds some of the most sensitive data a firm has, including performance evaluations and candidate records, so every design decision has to hold up under that scrutiny. And we are embedding AI directly into evaluation and staffing workflows, which is a real engineering problem rather than an API call. This is an individual contributor role with organization-wide influence: you will not manage people, but your designs and standards will shape how the whole team builds.

Requirements

10+ years of professional software engineering experience, including 3+ years at a staff, principal, or equivalent architect level
Demonstrated ownership of the architecture of a production SaaS product at scale, including living with those decisions over multiple years
Experience taking a new platform from initial design to production, not only extending established ones
Experience building software that handles sensitive personal data under real compliance obligations, and operating what you build in production
Track record of raising technical quality across teams you did not manage
Expert-level proficiency in TypeScript and Node for production services, including async failure modes, a modern server framework (NestJS, Fastify, Express, or similar), and performance under load
Deep MongoDB expertise: document modeling, embedding and referencing trade-offs, indexing and query optimization, the aggregation framework, transactions, change streams, and schema migration. Production operations experience including replica sets, sharding, and performance profiling
Strong proficiency in modern React, and deep API design experience across REST and gRPC, including versioning and backward compatibility
Practical experience building LLM-backed product features: prompt and context engineering, retrieval, structured output, and output evaluation
Enterprise integration experience: REST and SOAP APIs, OAuth 2.0, webhooks, and batch and delta sync against systems you do not control
Multi-tenant SaaS architecture, including tenant isolation, per-tenant configuration, and zero-downtime deployment
Proficiency across the AWS application platform: EKS or ECS/Fargate, Lambda, MongoDB Atlas, S3, EventBridge, SQS, Step Functions, API Gateway, IAM, Secrets Manager, and Bedrock or comparable managed LLM services
Infrastructure as code, CI/CD, and Kubernetes at production scale (Terraform, GitHub Actions, GitOps), with strong observability practice
Application security fundamentals: authorization models, OWASP risks, data protection, and secure SDLC practices

Nice To Haves

Experience in HR technology, talent management, or people analytics
Experience in legal technology, or another regulated enterprise domain
Production experience with Go
Experience migrating a relational data model to a document model, or replatforming a legacy on-premises product, and honest views on what that costs
Experience with MongoDB Atlas capabilities such as Atlas Search, Vector Search, Queryable Encryption, and Global Clusters for data residency
Experience with responsible AI practice in a high-stakes context: bias and fairness evaluation, explainability, and human-in-the-loop design
Experience integrating with Workday or comparable enterprise HRIS platforms
Working knowledge of GDPR, SOC 2, and international data residency requirements
Computer Science or Engineering degree, or equivalent practical experience

Responsibilities

Own the end-to-end architecture: service decomposition, API strategy, and the platform foundations the product will sit on for years
Own the MongoDB data architecture, including document modeling, indexing strategy, schema evolution, and the tenant isolation model. These are the hardest decisions to reverse once customer data is in production
Own the migration and coexistence strategy from the current vi products, covering data migration and phased customer transition
Set the technical strategy for AI-enabled features: model selection, prompt and context design, output quality evaluation, cost and latency, and the guardrails appropriate to performance and staffing decisions
Architect for a deeply configurable product without fragmenting the codebase or making every release a regression risk
Define the architecture for data privacy and access control: role-based and record-level permissions, evaluation confidentiality, data residency, and auditability
Lead architecture and design reviews, and champion Continuous Delivery and disciplined use of AI-assisted development
Design, build, and ship production TypeScript/Node services, Go services where the platform calls for it, and the React front ends they serve. You will be in the codebase every week
Design document schemas and indexes that hold up under real query patterns, and write the aggregation pipelines behind reporting and analytics
Build the integration surface that makes the product viable inside a firm: HRIS and payroll systems (Workday and equivalents), matter data, SSO and directory providers, and recruiting feeds
Build LLM-backed capabilities such as evaluation drafting assistance, sentiment analysis, and feedback summarization, including the evaluation harnesses that tell us whether quality is improving
Design event-driven workflows using SQS, Step Functions, Lambda, and change streams
Engineer for the seasonality of talent work: review cycles concentrate enormous load into short windows, and the system has to hold up on the worst week of the firm's year
Take part in on-call and incident response for what you design
Mentor senior and mid-level engineers through design pairing, code review, and direct coaching
Partner with Product Management, UX, and QA from discovery through release
Work with DevOps and Platform teams on CI/CD, infrastructure automation, and cloud cost efficiency
Translate technical trade-offs into terms executives and non-technical stakeholders can act on
Raise the hiring bar by interviewing, assessing, and helping onboard engineers