• Design, develop, and maintain backend services using Node.js 22 and TypeScript 5.5. • Build and manage database schemas, migrations, and data access layers using Prisma ORM. • Design and maintain domain-driven microservices with clear service boundaries and ownership. • Develop and support REST APIs for internal service-to-service communication. • Implement and maintain asynchronous processing workflows and event-driven architectures. • Apply CQRS principles to separate transactional and reporting workloads. • Implement reliable data consistency patterns, including the Transactional Outbox Pattern. • Collaborate with engineering teams on architecture, code quality, and system scalability initiatives.

Role Description Foresite is looking for a Senior Software Engineer - AI Integration with strong, hands-on AI experience to help shape how AI gets built into our platform. We are a Managed Security Services Provider (MSSP) building the next generation of AI-powered security operations. What You'll Do: - Design and ship the systems that connect LLMs to real security workflows — from RAG pipelines over threat intelligence to agentic automation that handles triage and investigation steps that currently require human effort. - Influence our AI architecture, product direction, and the standard for how the team builds with LLMs going forward. - Design and build AI-powered workflows that serve both internal analysts and external customers across guided security operations. - Own the AI architecture end-to-end: model selection, prompt engineering, RAG pipelines, agent orchestration, and evaluation frameworks. - Optimize for cost and performance — manage token budgets, reduce latency, and build instrumentation so we know exactly what our AI spend buys us. - Collaborate with product and engineering to identify where AI creates real leverage and where it doesn't. - Mentor engineers on LLM best practices and raise the AI literacy of the broader team. Qualifications - 5+ years of software engineering experience with strong fundamentals (you write production code, not just notebooks). - Deep, practical experience using Agent Development Kit. - Proven track record of integrating LLMs into production environments - prompt engineering, context management, RAG architectures, agent frameworks, evaluation and observability. - Deeply proficient in React 18/19 and TypeScript; comfortable with React Router v7 and modern routing patterns. - Comfortable designing schemas, writing queries, and reasoning about performance across PostgreSQL and Firestore. - Experience designing secure multi-tenant AI architectures; understanding of how to build LLM integrations that enforce strict data isolation between customers. - Strong understanding of scalable and highly available cloud-native system design. - Experience working closely with product teams to ship user-facing features. Requirements - Knowledge of Infrastructure as Code (IaC) using Terraform to automate, orchestrate, and manage cloud platform resources effectively. - Familiarity or hands-on experience with Google Cloud Security products (e.g., Security Command Center, SecOps, Mandiant). - Experience building autonomous AI agents, multi-modal applications, or complex prompt orchestration pipelines. Benefits - Mission-driven partner helping organizations navigate an increasingly complex threat landscape. - Part of a "humans-first" culture where your expertise is valued, and your well-being is a priority. - Leverage Google Cloud Premier SecOps Partnership to stay at the cutting edge.

Role Description The Development Team Lead – AI Team is a hands-on technical leadership role responsible for guiding development of AI-powered applications and platform capabilities while remaining actively involved in engineering execution. This role combines software delivery, AI platform adoption, and team leadership. - Lead delivery of AI-powered product capabilities - Provide day-to-day technical leadership and coordination for an agile engineering team - Remain deeply involved in implementation and architecture - Guide adoption of practical AI engineering patterns - Mentor engineers and improve engineering quality - Partner with platform, infrastructure, and product teams Qualifications - 8+ years of software engineering experience with deep knowledge of C#, .NET, .NET Core and modern application frameworks - Experience with React.js, TypeScript/JavaScript, SQL, and APIs - Experience building AI-powered applications or integrations - Experience with AI development tools and methodologies - Strong cloud (Azure/AWS), API, and distributed systems knowledge - Experience mentoring engineering teams - Strong communication and technical leadership skills

• Build and maintain backend services and APIs in Java • Work across multiple microservices (3-4) simultaneously • Collaborate closely with Product Owners on technical direction • Contribute to cloud-native architecture on AWS (90%) + Azure (10%) • Deploy and operate services using Kubernetes and Docker (must-have) • Contribute to Python-based services when needed • Work with analytics and data insights to support decisions • Follow SDLC best practices: testing, code reviews, documentation • Collaborate with DevOps on CI/CD, deployments, scaling