Head of DaaS Strategy & Operations
Partner with customers to build and deploy Generative AI and machine learning solutions from use case scoping and data exploration to model development and deployment, leveraging Snorkel Flow or designing custom approaches. Develop and implement state-of-the-art AI systems including retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes, and agentic workflows. Create augmented real-world datasets and evaluation workflows to ensure model reliability and transparency. Manage relationships with customers' leadership and stakeholders to ensure successful AI project development and deployment. Collaborate with pre-sales Solutions and Product teams to map customer needs to capabilities and prioritize roadmap gaps. Work with other Applied AI Engineers to standardize solutions and contribute to tooling and best practices. Lead stakeholder education on AI quantitative capabilities and serve as the voice of customers for AI paradigms and workflows. Conduct enablement workshops for knowledge transfer to customers using Snorkel AI. Annual travel up to 25%.
QA Engineer, AI
The QA Engineer, AI is responsible for owning and expanding the end-to-end automated test suite using frameworks like Playwright, Jest, and Vitest across all deployment surfaces including web app, iPad, Epic, Cerner, Surgery Connect, EMIS, and multiple browsers. They design test cases covering functional requirements, edge cases, and failure modes, integrate tests into CI pipelines to gate every PR, and use AI coding agents to accelerate test creation and maintenance. They build end-to-end simulation suites for clinical AI pipeline evaluation, create smoke tests, collaborate with the ML team on AI output evaluations, and detect quality regressions. The role involves managing the QA process for versioned releases, running regression and manual exploratory tests, managing release checklists, maintaining requirements traceability matrices linking software requirements to test cases and results, supporting audits with documentation, automating compliance workflows, logging and triaging defects, working with developers to reproduce issues and verify fixes, and ensuring no high-severity defects ship without resolution and re-testing.
People Programs Manager
Partner with customers to build and deploy impactful Gen AI and machine learning solutions, including use case scoping, data exploration, model development, and deployment. Develop and implement state-of-the-art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes, and agentic workflows. Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. Manage relationships with customers' leadership and stakeholders to ensure successful AI project development and deployment with Snorkel Flow. Collaborate with pre-sales Solutions and Product teams to map customer needs to capabilities, prioritize roadmap gaps, and guide project setup. Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices. Lead stakeholder education on quantitative capabilities and help them understand different AI approaches. Serve as the voice of customers for new AI paradigms, data science workflows, and provide customer feedback to product teams. Conduct enablement workshops to transfer knowledge to customers using Snorkel AI. Annual travel up to 25%.
AI Engineer
Design multi-agent systems with Subagents/Handoffs/Router patterns, implement agent logic using langchain/langgraph, design comprehensive evaluation frameworks, optimize prompts with A/B testing, implement state management (short-term and long-term memory), and design RAG patterns with vector store integration. Guide customers on agent deployment and configuration management, integrate agents into CI/CD pipelines, collaborate with Solution Architects on infrastructure requirements, and set up observability using LangSmith. Lead agent engineering maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Solution Architects, Engagement Managers, and Product/Engineering teams.
Senior AI Engineer - Agent Team
Set up end-to-end evaluations to measure and improve agent performance. Experiment with new agentic techniques such as multi-agent systems and reasoning-from-feedback (RFT). Build lightweight tools, servers, and orchestration layers like MCP servers that enable agents to operate reliably in production. Stay on top of emerging research and blogs on LLM/AI agents and bring ideas into production experiments.
Audio Engineer
The Audio Engineer will own and scale audio quality across voice AI products, ensuring voices sound great to human listeners across thousands of voices and recording conditions. Responsibilities include identifying and correcting audio artifacts, loudness inconsistencies, frequency imbalances, and sibilance issues in large-scale voice datasets; designing and implementing scalable audio processing pipelines including EQ, compression, de-essing, dynamic range optimization, and normalization strategies; optimizing audio quality across real and synthetic voices for consistent product experience; leading audio quality decisions during on-site voice actor recording sessions such as microphone selection, placement, gain staging, and environment setup; defining, documenting, and enforcing audio quality standards for external vendors to meet training and product needs; converting manual audio workflows into automated, repeatable, code-based systems; collaborating with research to improve training data quality, especially TTS speaker-specific fine-tuning; and contributing to synthetic data pipelines by defining and validating acoustic characteristics and guiding sound profile production and evaluation.
Healthcare & life sciences AI agent analyst (contract)
Develop and implement AI agents for life sciences applications, including medical writing assistants, literature synthesis tools, regulatory document preparation systems, and research protocol generators. Design and execute comprehensive testing protocols to evaluate AI agent performance, scientific accuracy, and adherence to medical writing standards across diverse research and regulatory scenarios. Collaborate with Customer Operations and Life Sciences Industry leaders to translate research workflows, regulatory requirements, and publication standards into functional AI agent specifications. Guide technical and engineering teams in implementing best practices for medical AI development, including prompt engineering, retrieval-augmented generation, and scientific validation methodologies. Potential additional responsibilities include architecting and deploying multi-agent systems to orchestrate complex research workflows, leading research initiatives on novel applications of generative AI in medical writing, drug development, and scientific research, publishing findings, and providing training and mentorship on life sciences AI development principles, scientific integrity considerations, and regulatory compliance.
Senior Forward Deployed Engineer
As a senior Forward Deployed Engineer, the role involves embedding with enterprise customers such as Am Law firms, in-house teams at large enterprises, and other professional services organizations to develop cutting-edge AI systems into production-grade workflows that deliver measurable outcomes quickly. Responsibilities include mapping out workflows with customers, de-risking constraints, defining success metrics for custom builds, and designing, prototyping, and productionizing custom workflows by customizing knowledge sources, retrieval pipelines, tool use/agents, prompts, and guardrails to ensure reliability, observability, and scalability. The role also requires integrating workflows with client systems and data sources, building and maintaining evaluations and harnesses to capture real-world quality on a client basis, and feeding those signals into iteration loops and model choices. Additional responsibilities include operationalizing adoption through training, creating runbooks, and delivering durable playbooks to customer champions and Harvey product/engineering teams to ensure scaling beyond individual accounts, as well as surfacing field patterns that inform platform capabilities and future product development.
Founding Engineer, Dubai
Design and develop custom AI solutions tailored to the unique needs of customers, ensuring seamless integration and scalability. Partner with a high-caliber team across the full project lifecycle, including requirements gathering, prototyping, system design, coding, testing, deployment, and support. Actively shape the engineering and broader company culture, influencing areas such as learning, hiring, and celebrations. Work closely with clients to understand their needs, participate in regular meetings and standups, and contribute to discussions around technical feasibility and project tradeoffs.
Evaluation Scenario Writer - AI Agent Testing Specialist
Contributors create structured test cases that simulate complex human workflows, define gold-standard behavior and scoring logic to evaluate agent actions, analyze agent logs, failure modes, and decision paths, work with code repositories and test frameworks to validate scenarios, iterate on prompts, instructions, and test cases to improve clarity and difficulty, and ensure that scenarios are production-ready, easy to run, and reusable.
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