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Handshake is a career platform powering 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, the company launched Handshake AI, a rapidly growing business that has scaled from $0 to ~$1B run rate by partnering with frontier AI labs to create evaluations, benchmarks, and training data at scale.
You will join the Backend Platform team as a Senior Software Engineer, initially focused on supporting Handshake AI and internal AI initiatives. Your primary responsibility is building and maintaining backend services, shared platform capabilities, and developer tooling that power HAI's products and the company's internal AI work. The role centers on core backend platform concerns—service architecture, APIs, data systems, performance, reliability, and developer experience—with increasing use of LLMs and agentic systems.
Key responsibilities include:
- Design, build, and operate backend services and APIs supporting HAI products, primarily within a full-stack TypeScript repository
- Develop shared libraries, services, and architectural patterns to reduce duplication and improve extensibility
- Improve performance, scalability, reliability, and observability of HAI's backend systems
- Lead work on database design, data access patterns, query performance, indexing, caching, and data model evolution
- Identify recurring product-engineering problems and convert them into reusable platform capabilities
- Make sound architectural decisions balancing delivery speed, performance, maintainability, and operational cost
- Contribute directly to internal AI initiatives, including shared capabilities for building, evaluating, and operating LLM-powered and agentic systems
- Partner with Developer Platform teams (ML, Cloud Engineering) on model and service integration, orchestration, evaluation, observability, and failure handling
- Participate in technical planning, design reviews, code reviews, operational support, and incident response
- Mentor other engineers and establish practical backend engineering standards
The strongest candidates combine strong backend fundamentals with practical knowledge of LLM-powered and agentic systems. Success requires the ability to design and operate systems around AI-powered product experiences, not necessarily expertise in every model or framework.
REQUIREMENTS:
- 5+ years of professional software engineering experience, primarily in backend or platform engineering
- Experience designing, building, and operating production services and APIs
- Strong understanding of distributed systems, data modeling, service boundaries, common backend architecture patterns, and reliability/performance tradeoffs
- Deep TypeScript and Next.js experience strongly preferred; must be comfortable navigating a full-stack TypeScript repository and contributing across boundaries
- Strong experience with relational databases: schema design, query optimization, indexing, transactions, and diagnosing database performance issues; PostgreSQL experience especially relevant
- Familiarity with backend technologies such as Temporal, Redis, Elasticsearch, GraphQL, or event-driven systems
- Experience operating services in cloud and containerized environments (GCP, Kubernetes, Terraform, Docker)
- Practical knowledge of LLM-powered systems: model and tool integration, RAG, agent orchestration, prompt management, evaluation, and observability
- Record of independently driving ambiguous projects from problem definition through production rollout
- Strong communication skills and ability to collaborate with product engineers and cross-functional teams
- Sound technical judgment and preference for understandable, maintainable systems
BONUS:
- Direct production experience with ML, LLM, or agent-powered product features
- Experience with LLM orchestration frameworks or agent architectures involving tool use, memory, and multi-step workflows
- Experience building internal AI tools or shared AI capabilities for other engineers
- Experience creating internal platforms, paved paths, or self-service tools
- Experience modernizing mature backend systems while supporting active product development
- Experience with event-driven architecture or high-throughput data systems
