AI Software Engineer Jobs

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The Platform Incubation Engineer role within Forward Deployed Engineering (FDE) involves architecting and building new platform capabilities by turning frontier customer signals into concrete designs, implementations, and APIs. Responsibilities include incubating platform bets end-to-end by forming hypotheses, shipping initial capabilities, and iterating based on real usage feedback. The engineer will embed with design partners to conduct technical discovery and translate needs into product and platform requirements, partner with customer-tagged FDEs to deploy, debug, capture repeatable patterns, and improve the platform based on field learnings. They will also design and run pilot programs, collaborate closely with core product and engineering teams to align architecture and production efforts, and drive adoption outcomes by measuring usage, identifying blockers and failure modes, and prioritizing platform increments to unlock repeatable value.

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Design and deliver production-grade AI agents for healthcare that handle sensitive patient and member interactions while maintaining strict HIPAA compliance. Drive the Agent Development Life Cycle with ownership from pilot through deployment and iteration. Partner with healthcare leaders to understand challenges and build AI agents that address operational needs. Develop expertise in healthcare systems, workflows, and data/privacy standards to create trustworthy AI experiences. Guide and contribute to the evolution of Sierra's core platform based on customer feedback. Examples of projects include building AI agents for insurance networks, providers, primary and urgent care clinics, and healthcare financial platforms, as well as experimenting with voice models for secure interactions.

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Design and deliver production-grade AI agents for healthcare that handle sensitive patient and member interactions while maintaining strict HIPAA compliance. Build and ship highly performant, reliable, and empathetic AI agents that help with understanding coverage, finding providers, scheduling appointments, navigating billing, and more. Have complete ownership and autonomy over the Agent Development Life Cycle from pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production environments serving healthcare payers, providers, and platforms. Work directly with healthcare leaders including executives and technical teams at health plans, provider networks, and healthcare technology companies to understand and solve their most pressing challenges. Develop deep expertise in healthcare systems and workflows, including integrations across EHR and patient access platforms, payer and provider operations, and healthcare data and interoperability standards. Translate complex healthcare knowledge into trustworthy AI experiences. Use customer insights to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape the future of AI agent development in healthcare.

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Build and operate backend systems that serve AI-powered features in production; design inference pipelines, orchestration layers, and service boundaries around models; own production concerns including monitoring, logging, alerting, and incident response; optimize latency and throughput across inference, caching, batching, and streaming.

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Build and operate backend systems that serve AI-powered features in production. Design inference pipelines, orchestration layers, and service boundaries around models. Own production concerns including monitoring, logging, alerting, and incident response. Optimize latency and throughput across inference, caching, batching, and streaming.

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Own customer outcomes end to end by working directly with customers, design partners, and internal stakeholders to define technical scope, success criteria, and delivery milestones, then building and shipping the solution. Design and implement features across the full stack with a focus on solving real problems observed in production environments. Integrate deeply with customer environments by working hands-on with cloud platforms, observability systems, CI/CD pipelines, and incident response workflows to ensure product fit. Diagnose and resolve complex issues across customer deployments, turning support interactions into product insights and durable fixes. Build evaluations and feedback loops to quantify customer value and ensure new capabilities are genuinely impactful. Write clean, maintainable, well-tested code, lead design discussions and code reviews, and help shape the technical direction of the product and the engineering culture of the team.

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The Engineering Manager, Product at Harvey is responsible for owning end-to-end delivery of core product initiatives, from technical design through execution and iteration, while managing a high-performing fullstack engineering team. This includes setting technical direction for large-scale, AI-powered systems such as retrieval over petabyte-scale document collections, product interfaces for AI collaboration, long-horizon planning agents for critical workflows, government-grade security for sensitive data, evaluation of LLMs across extensive taxonomies, and internet-scale data collection across multiple jurisdictions. They must translate product vision into architecture balancing speed, quality, and scalability, lead hands-on contributions to design, code, and architecture reviews, and actively engage in implementation to unblock the team or solve difficult problems. Additionally, they build and grow the team by hiring engineers, setting technical and behavioral standards, and mentoring for career development. The role involves close partnership with Product, Design, and AI teams to identify opportunities and deliver intuitive user experiences, establishing an engineering culture focused on simplicity, ownership, craftsmanship, and continuous improvement, and aligning execution with company goals to support product strategy and long-term impact.

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As a Platform Engineer Intern, you will design and build a low latency, scalable, and reliable model inference and serving stack for cutting edge SSM foundation models. You will work closely with the research team and product engineers to translate research into products. Additionally, you will build highly parallel, high quality data processing and evaluation infrastructure for foundation model training.

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As a Senior Software Engineer at Neara, you will design and implement features in one of three engineering groups: Digitisation, Platform, or Design. In Digitisation, responsibilities include developing and measuring algorithmic and machine learning improvements to digital twin extraction, improving monitoring systems to identify extraction errors, and creating tooling to quickly fix problems from automated solutions. In Platform, duties involve developing the internal platform functionality by identifying common abstractions for varied use cases and creating data abstractions that allow users to semantically model and interact with organizational data. In Design, tasks include developing solutions for simulating structural forces on electric networks and their behavior in different weather scenarios, as well as developing CAD-like tools to import engineering designs and integrating lidar and imagery for better simulation outcomes.

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Build internal and customer facing tools used daily to improve AI agent behavior. Drive product features from intuitive React frontends (TypeScript) to robust Python (Django/FastAPI) backends. Build the workflows that allow human-in-the-loop AI to function at peak efficiency. Set the standard for code quality and scalability in a fast-moving, early-stage product environment. Influence product direction, technical standards, and architectural decisions from day one.