SQL AI Jobs

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As a 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 scaling document ingestion and processing growing at 10x every 6 months, designing massive data collection from over 50 legal jurisdictions, building government-level security for top governments and firms, leading projects that enhance AI experiences across web, desktop, mobile, Google Docs, MS Word, and API platforms. Additionally, you will build AI-platform and AI-native features like agentic orchestration layers, tool calls, and retrieval systems, and ship across the full stack using React and TypeScript on the frontend alongside Python and Postgres on the backend to create intuitive UX and robust APIs for streaming results, long-running processes, and complex tool-calling workflows.

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As a Protection Scientist Engineer within Integrity and Investigations at OpenAI, you will be responsible for designing and building systems to proactively identify and enforce on abuse on OpenAI’s products. This includes ensuring robust abuse monitoring for new products, sustaining monitoring for existing ones, and prototyping and incubating defense systems against highest risk harms. You will respond to and investigate critical escalations that are not caught by existing safety systems. The role involves scoping and implementing abuse monitoring requirements for new product launches, improving processes to sustain monitoring operations for existing products by developing automation approaches, and maturing systems for detection, review, and enforcement of abuse for major harms. You will work cross-functionally with product, policy, operations, investigative, and engineering teams to understand risks, secure sufficient data, and build scaled tooling. The role includes participation in an on-call rotation for resolving urgent escalations and may involve investigation of sensitive content including sexual, violent, or disturbing material.

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Architect and develop robust backend systems that integrate with LLM APIs to power Clarium's AI features. Design and build scalable backend services in Python and FastAPI. Take full ownership of critical system components from REST APIs to AI agent implementation. Collaborate with product managers and customers to ensure what you build maps directly to real-world healthcare workflows. Participate actively in code reviews and sprint planning.

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As a Sr. Applied AI Engineer, you will build reusable AI products by acting as the product owner for your application area, designing, developing, and deploying robust, repeatable Generative AI agents that serve as configurable solutions for customers. You will partner with Solution and Forward Deployed Engineers during sales and implementation projects to understand customer needs, develop standard templates and reusable components to reduce time-to-activation, and solve core challenges. You will synthesize customer feedback to form a clear vision for your agents, iterate on solutions to solve concrete use cases at scale, and treat each agent as a product itself. Additionally, you will collaborate closely with the core product team to prioritize platform features that unblock application development and serve as an expert user consultant during new feature development.

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As a Sr. Applied AI Engineer at Taktile, the responsibilities include building reusable AI products by acting as the product owner for application areas, designing, developing, and deploying robust generative AI agents as configurable solutions for customers. The role requires partnering with Solution and Forward Deployed Engineers during sales and implementation projects to understand customer needs in depth, and developing standard templates and reusable components to reduce activation time and address core challenges. The engineer must synthesize customer feedback into a clear vision for AI agents, iterating solutions to solve concrete use cases at scale, treating every agent as a product itself. Collaboration with the core product team is essential to prioritize platform features that support application development and acting as an expert user consultant during new feature development.

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Design and build the backend systems and services that power Sesame's product, including data models, APIs, and distributed systems. Write durable software focusing on scalability, reliability, and correctness rather than prototyping. Build and evolve frameworks and libraries for other engineers to use, emphasizing good software design. Own the full lifecycle of services, including schema design, implementation, deployment, performance tuning, and on-call responsibilities. Work with various data stores such as relational databases, NoSQL, queues, caches, and search indexes. Identify and resolve performance bottlenecks while considering cost, throughput, and latency. Architect systems where machine learning models are a key component but not the sole aspect, such as real-time audio pipelines, agentic orchestration, and stateful conversation systems. Identify opportunities to improve developer efficiency through prototyping tools or workflow improvements and collaborate with the infrastructure team to productionize them.

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Design and implement LLM guardrails that detect abuse scenarios in AI-generated code and agent interactions. Build AI-powered detection systems that use LLMs to identify malicious patterns, classify threats, and automate response decisions. Build and operate abuse detection systems that identify phishing, cryptomining, account takeover, and financial fraud across millions of daily user actions. Design automated response mechanisms that enforce platform policies without manual intervention. Own the full abuse response lifecycle: detection, investigation, enforcement, and handling appeals alongside Support and Legal. Analyze attack patterns using BigQuery and Hex, turning investigation findings into new detection rules. Maintain and extend internal detection tools (Slurper, Netwatch) that continuously monitor user activity. Integrate and tune security scanners (SAST, SCA) in CI pipelines with tight performance SLAs. Track abuse trends, measure detection effectiveness, and adapt defenses as attack patterns evolve.

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The Agentic Finance Engineer is responsible for designing, building, and maintaining a reliable financial data foundation using modern tools, covering revenue, AP/AR, procurement, close, strategic finance, and FP&A. They will partner closely with the data infrastructure team to build the financial data model, define canonical datasets, dimensional schemas, and transformation logic for Finance stakeholders. This role includes partnering with Finance leads to translate business requirements into technical architecture, building and maintaining dashboards and self-serve reporting tools to provide real-time visibility into key metrics. The engineer will own the Agentic Finance roadmap, prioritize use cases, and drive features from ideation to deployment, identifying high-value automation opportunities across Finance and corporate operations, and shipping solutions to eliminate manual work. They will build intelligent, reliable automation using agents, AI-powered tools, multi-step ETL jobs, and internal tooling that Finance teams use, such as lightweight apps, workflow automations, and AI-assisted processes. The engineer must enforce data integrity standards and testing practices to ensure auditability and reliability, ensure AI-assisted processes meet governance and controls standards with clear auditability, and champion a culture of data quality and documentation so that Finance teams trust and rely on the systems built.

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As the Senior Manager of Data Science at Abridge, the responsibilities include building and managing a world-class team of data scientists, providing guidance, mentorship, and setting high standards. The role requires fostering a collaborative team culture focused on agency and clarity of thought, driving product strategy through data-driven insights across the product portfolio, and analyzing user behavior and product performance metrics. It involves partnering with product, strategy, and research teams to develop ROI frameworks for customers by ingesting real-time data to demonstrate impact. The role also includes collaborating with the research team on models and model evaluation, shaping evaluation frameworks, monitoring production performance, and defining clinical quality metrics. The Senior Manager must communicate data strategy, complex analyses, and insights to cross-functional partners and the executive team, structure the company's data strategy alongside Data Engineering by identifying data gaps and optimizing data use, make critical technical infrastructure decisions including tooling choices and technical standards, and build the data science organization to incorporate best practices and AI to accelerate data ingestion and insight generation.

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As an Abuse Investigator focused on AI Self-Autonomy and Agentic Risk on the Intelligence and Investigations team, you will be responsible for identifying and investigating cases where models exhibit autonomous or agentic behavior, including chaining capabilities, acting with increasing independence, or demonstrating patterns that may introduce safety risk. This includes detecting behaviors that are not explicitly intended, understood, or covered by existing safeguards. You will review leads, investigate model behavior, and identify cases where systems demonstrate agentic or autonomous patterns that introduce safety risks. You will detect and analyze behaviors such as multi-step planning, capability chaining, tool use, persistence, and workaround behavior. You will develop signals and tracking strategies to help proactively identify emerging agentic risk patterns across the platform. You will identify gaps in existing safeguards, evaluations, or monitoring systems and propose improvements. You will communicate investigation findings clearly to technical, policy, and leadership stakeholders. This role involves working in high-pressure environments and interacting with others effectively.