SQL AI Jobs

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Design and build production systems end-to-end across frontend applications, backend services, APIs, data models, and developer tooling. Develop new vertical product capabilities involving document ingestion, workflow orchestration, retrieval, structured outputs, agent frameworks, and human-in-the-loop review flows. Build and operate data-intensive systems, including ETL pipelines, analytical data models, serving layers, and interfaces for querying and exploring large datasets. Work across a modern technical stack that may include Python, TypeScript, SQL, cloud infrastructure, agent orchestration engines, data processing platforms, and analytical databases. Define service boundaries, schema design, and system architecture for new product areas with an emphasis on reliability, extensibility, and speed of iteration. Ship customer-facing features quickly, then harden them for scale through observability, testing, performance tuning, and operational excellence. Partner directly with customers and internal stakeholders to understand domain-specific workflows, map requirements into technical designs, and iterate rapidly on real usage. Build evaluation, monitoring, and feedback systems that measure product quality in production and inform engineering and model decisions. Contribute reusable platform patterns, abstractions, and internal tools so successful solutions can scale across customers and verticals. Help drive technical direction in ambiguous spaces, making strong engineering decisions with incomplete information and a high degree of ownership.

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As an AI Strategist in Healthcare, you will lead and drive technology solutions within the healthcare vertical and manage the go-to-market (GTM) process with healthcare client engagements from initial meetings through deal closure. Responsibilities include diagnosing client problems through an AI perspective, designing data-driven AI strategies to transform operations and improve outcomes, and rapidly building demos and proof-of-concept solutions on the Distillery platform to demonstrate capabilities to prospective healthcare clients. You will work at the intersection of business strategy and AI implementation by bridging the gap between technical AI tools and business outcomes, collaborating closely with healthcare subject matter experts, and taking ownership of the entire pre-sales process including discovery, solution architecture, and feasibility. Additional duties involve researching clients and their industry landscapes to tailor use case materials, feeding insights to account executives to refine pitches, co-designing solutions with engineering, navigating enterprise data constraints to produce reliable AI outcomes, creating compelling AI ROI storylines and decks, developing reusable GTM assets, maintaining pre-sales account documentation, and ensuring formal handoff to expansion teams.

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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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The AI Evaluation Engineer will analyze training and evaluation datasets to identify distributional gaps, labeling inconsistencies, and long-tail opportunities; design and execute labeling campaigns including the development of golden datasets and annotation guidelines; build and maintain dashboards to track model accuracy, regression trends, and product-specific KPIs; investigate failure modes through prompt clustering, error taxonomy development, and user intent classification; operationalize feedback loops by mining product telemetry and human-in-the-loop reviews for signal and translate these into data-driven model improvement strategies; partner with engineers and product managers to run structured A/B tests and human evaluations for new models or features; support the development of scalable data and evaluation infrastructure for LLMs and agents; and work with product, engineering, and legal teams to create clear and transparent processes for handling customer data in AI training, fine-tuning, and evaluation.

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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.