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. **Responsibilities** **Technical Leadership** - 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 **Hands-On Engineering** - 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 **Collaboration and Mentorship** - 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 **Required Qualifications** - 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 **Preferred Qualifications** - 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 **Technical Environment** - **Backend: **TypeScript/Node and Go services - **Front End: **React, TypeScript - **Data: **MongoDB Atlas, S3 - **Compute: **Kubernetes, Lambda - **AI: **Amazon Bedrock and managed LLM services, vector search, prompt and evaluation tooling - **Integration: **EventBridge, SQS, Step Functions, API Gateway, REST and gRPC, change streams - **CI/CD: **GitHub, GitHub Actions, Terraform, FluxCD - **Observability: **Grafana Cloud, OpenTelemetry, CloudWatch - **Platform: **Stridyn, Aderant's shared cloud platform and common data plane - **Ways of working: **Pod-based delivery teams with embedded PM, UX, and QA; Continuous Delivery; "you build it, you run it"