Java AI Jobs

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Design, build, and scale AI-powered, user-facing products that enhance Eva's healthcare interactions. Lead end-to-end delivery of complex full-stack product experiences including frontend architecture, backend services, APIs, data integrations, and production workflows. Collaborate with Product, Design, Data Science, Infrastructure, and other engineering teams to integrate AI capabilities into user workflows. Translate product and AI opportunities into clear technical plans balancing speed, user experience, reliability, safety, and long-term maintainability. Build robust systems connecting application logic, data pipelines, model outputs, and human-centered product experiences. Evaluate and integrate AI technologies such as LLM-enabled workflows, retrieval systems, classification, summarization, automation, and decision-support experiences. Establish frontend and backend engineering standards, including component architecture, API design, system reliability, observability, testing, and development best practices. Make technical tradeoffs considering product impact, engineering complexity, scalability, and platform health. Drive cross-team and cross-organization alignment through technical clarity and collaboration. Mentor and grow engineers, improving technical execution, product thinking, and engineering culture. Contribute to technical roadmaps focusing on AI-enabled product development, platform scalability, and full-stack architecture. Help shape Eva's responsible AI use emphasizing usefulness, trust, reliability, and user experience.

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The role involves leading and growing Kalepa's Core Product team by defining the architectural roadmap, setting strategy, driving engineering operational excellence, and cultivating a high-performance, results-driven culture. Responsibilities also include establishing frameworks, engineering standards, and cross-functional cadences to power Kalepa's platform that supports human and AI underwriters. The position requires bridging the gap between product vision and technical execution to ensure technology investments drive business impact and long-term growth. The role demands managing both human and AI agents, ensuring quality and reliability, driving large-scale engineering initiatives, aligning technical strategy with company objectives, recruiting top-tier engineering talent, making tradeoffs to ship high-quality code in a fast-growing environment, championing metrics-driven decision-making, and implementing robust engineering practices. It also involves overseeing and scaling platforms using serverless technologies, asynchronous workflows, and modern cloud environments, and fostering a culture focused on experimentation and rapid iteration on unsolved problems.

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Apply software engineering skills to design and develop AI video editing products; prototype and craft innovative products for prosumers and enterprise customers; work with cross-functional teams to brainstorm, plan, and deploy product features; design and implement A/B tests to understand the impact of changes, using data-driven insights to inform decisions and strategy adjustments.

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You will be responsible for defining operational domains and evaluating the reliability of the AI capabilities developed in-house. You will develop and extend the state-of-the-art in uncertainty quantification and uncertainty calibration. This will involve understanding the AI systems built, interfacing with them, and evaluating their robustness in real-world and adversarial scenarios. You will contribute to impactful projects and collaborate with people across several teams and backgrounds.

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As a Principal Engineer at Ironclad, you will collaborate cross-functionally with product managers, designers, and other engineers to spec, design, architect, and build features and systems. You will own and evolve core platform architecture including service boundaries, data models, multi-tenant scale, and reliability to support AI capabilities safely and efficiently across the product surface area. Additionally, you will partner with quality engineers to define, build, and maintain testing strategies. You will lead technical discussions, mentor and provide thoughtful feedback to other engineers on the team, and grow the team by interviewing and recruiting talented engineers. Your technical work will involve building AI solutions and applying AI tools and features such as large language models, retrieval-augmented generation, semantic search, and classification to power contract intelligence. You will drive end-to-end delivery of AI-powered product experiences, from problem definition and experimentation to reliable, scalable production systems, working on a modern technology stack including TypeScript, ReactJS, Node.js, Java, and Docker containers in Kubernetes on Google Cloud Platform (experience with these specific technologies is not required).

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As a Backend Software Engineer on the Product Engineering team at Harvey, you will own and lead engineering projects across various product lines. You will work closely with AI, Legal, and GTM teams to build secure systems that deliver value to customers. Responsibilities include retrieval over peta-byte scale documents, building organizational-level interfaces to collaborate with AI, managing dedicated GPU capacity across multiple regions, developing 1000-step planning agents that assist companies in going public, implementing government-level security for sensitive matters, evaluating large language models (LLMs) across a taxonomy of tasks, and internet-scale data collection from over 50 jurisdictions.

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As a Backend Software Engineer on the Product Engineering team at Harvey, you will own and lead engineering projects across various product lines. You will work closely with the AI, Legal, and GTM teams to build secure systems that deliver value to customers. Responsibilities include retrieval over peta-byte scale documents, creating organizational-level interfaces to collaborate with AI, managing dedicated GPU capacity across 5+ regions, developing 1000-step planning agents that help take companies public, ensuring government-level security for highly sensitive matters, evaluating large language models across a 10k+ leaf taxonomy of tasks, and conducting internet-scale data collection from over 50+ jurisdictions.

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Translate business requirements into requirements for AI/ML models; prepare data to train and evaluate AI/ML/DL models; build AI/ML/DL models by applying state-of-the-art algorithms, especially transformers; leverage existing algorithms from academic or industrial research when applicable; test, evaluate, and benchmark the AI/ML/DL models, and publish the models, data sets, and evaluations; deploy models in production by containerizing the models; work with customers and internal employees to refine the quality of the models; establish continuous learning pipelines for models with online learning or transfer learning; build and deploy containerized applications on cloud or on-premise environments.

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Responsibilities include translating business requirements into requirements for AI/ML models, preparing data to train and evaluate AI/ML/DL models, building AI/ML/DL models using state-of-the-art algorithms especially transformers, testing and evaluating models, benchmarking quality, publishing models and datasets, deploying models in production by containerizing them, working with customers and internal employees to refine model quality, establishing continuous learning pipelines with online or transfer learning, and building and deploying containerized applications on cloud or on-premise environments.

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The Backend Engineer is responsible for building systems that process and analyze millions of contracts reliably, designing pipelines that orchestrate large language models, data extraction, and clustering algorithms at scale, creating the most accurate search and retrieval systems on the market, and collaborating with lawyers and product teams to build new capabilities as large language models evolve.