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You will work end-to-end on the platform, contributing to the backend, frontend, infrastructure, and AI pipeline. You will own technical problems from initial discovery through to production deployment while shaping engineering standards.
You will design and deliver advanced agentic AI systems, including autonomous agents, graph-RAG pipelines, and high-performance Python services. You will also build interactive React-based interfaces to support engineers and analysts in their daily tasks.
The AI Frontend Engineer will lead the frontend architecture and development for a voice agent platform, ensuring intuitive and high-performance user interfaces. This role involves mentoring junior developers, collaborating with cross-functional teams, and integrating real-time voice technologies like WebRTC and WebSockets.
The AI Engineer will design, train, and optimize AI/ML models for voice agent platforms including STT, NLU, and TTS capabilities. They will also manage MLOps pipelines, develop APIs, and build frontend prototypes to support product development.
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Develop and integrate GenAI and LLM-based solutions into large-scale cloud-based SaaS production environments for healthcare. Lead technical architecture design, mentor senior team members, and collaborate across functions to deliver high-impact business outcomes.
The Customer Success Manager will engage with senior executives to develop tailored strategies and success plans that drive the adoption of legal AI solutions. They will also lead executive business reviews, manage customer retention, and act as a voice for the customer to internal product and engineering teams.
Design and implement AI-powered solutions for legal workflows such as contract review and discovery automation. Build scalable, secure AI systems and collaborate with cross-functional teams to deliver high-impact production-ready solutions.
The Implementation Consultant will guide corporate legal teams in adopting AI-powered solutions by designing workflows, configuring tools, and managing project delivery. They will also lead client training sessions and collaborate cross-functionally to ensure successful product adoption and client satisfaction.
Design end-to-end AI and generative AI solutions for healthcare provider use cases, including architecture, data flows, and integration patterns. Partner with clinical and operational stakeholders to identify high-value AI opportunities and define scalable implementation roadmaps.
The Forward Deployed AI Engineer will embed with strategic customers to design, pilot, and operationalize full-stack AI/ML applications and agentic systems. They will also standardize successful patterns into reference architectures and provide technical leadership to drive AI adoption.
The Sr. AI Engineer will design, build, and deploy production-grade AI-powered applications and automation solutions across the full stack. This role also involves providing technical leadership, mentoring team members, and establishing engineering standards to support the organization's AI transformation.
Develop and implement innovative compiler features and optimization passes using tools like LLVM and MLIR. Design new programming abstractions and optimize AI workloads for next-generation supercomputers and hardware accelerators.
The AI Deployment Engineer will design, develop, and deploy production software solutions that integrate AI and automation capabilities into manufacturing processes. This role involves collaborating with cross-functional stakeholders to translate operational needs into scalable, secure, and measurable technical applications.
The Technical Product Lead will own a product vertical end-to-end, managing strategy, technical design, and delivery. They are responsible for aligning cross-functional teams including engineering, compliance, and operations to ship reliable and secure financial products.
The Technical Product Manager will own a product vertical end-to-end, managing strategy, technical design, and delivery while aligning cross-functional teams. They are responsible for integrating AI, ensuring regulatory compliance, and maintaining system reliability across financial applications.
The Technical Product Manager will own a product vertical end-to-end, managing strategy, technical design, and delivery while aligning cross-functional teams. They are responsible for building reliable, regulatory-compliant financial products and integrating AI where it genuinely improves outcomes.
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You will design and implement integration and automation systems that orchestrate connectors and manage data streams. Additionally, you will be responsible for developing backend solutions and integrating LLM-driven processes into productive workflows.
Design and deliver end-to-end AI and generative AI solutions tailored for health plan use cases, including architecture, data flows, and deployment strategies. Partner with payer executives and cross-functional teams to identify high-value opportunities and define scalable implementation roadmaps.
The AI Engineering Specialist will develop internal platforms, frameworks, and accelerators to drive AI adoption at scale. They will also collaborate with global product and engineering teams to integrate AI solutions into the software development lifecycle.
You will embed with internal teams to identify operational friction and build production-grade agentic AI systems to automate workflows. Your work will involve creating end-to-end automation pipelines, internal developer tools, and data products that improve operational efficiency.
You will serve as the technical lead for the AI Platform team, owning the architecture and strategy for LLM-driven features. You will also act as a force multiplier by mentoring engineers and establishing high-quality technical standards across the team.
The role involves bridging the gap between business stakeholders and technical teams to identify and implement AI-driven automation opportunities. You will be responsible for documenting requirements, managing backlogs, and leveraging Generative AI tools to improve operational efficiency.
The Principal Engineer will lead the architecture for cloud-native, compliance-critical platforms, focusing on automation, workflow orchestration, and intelligent decisioning. They will collaborate across teams to modernize legacy systems, establish technical standards, and mentor engineering staff to ensure platform scalability and reliability.
You will partner with stakeholders to analyze and document AI automation requirements while mapping complex workflows for implementation. You will also define structured use cases, data flows, and API touchpoints to ensure seamless integration and delivery of AI-enabled solutions.
You will support the integration of generative AI technologies into existing software and develop new innovative AI-driven solutions. Additionally, you will assist in data preparation, software optimization using frameworks like LangChain, and cloud-native development projects.
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The Senior AI Applications Engineer will design, integrate, and productionize Generative AI solutions and traditional software applications to drive business value. The role involves leading end-to-end delivery, mentoring junior developers, and collaborating with cross-functional stakeholders to ensure high-quality UX and technical compliance.
Design, build, and deploy production-grade ML and LLM-based systems for enterprise clients while owning the technical delivery end-to-end. Mentor junior engineers and represent the company technically in client workshops and engagements.
The Lead Engineer will own the engineering, reliability, and lifecycle management of the enterprise agentic AI platform, including production AI agents and control plane infrastructure. They will establish engineering standards, manage FinOps for AI workloads, and lead a team to scale the practice while ensuring alignment with security and governance.
The Forward Deployed Engineer will partner with business leaders to identify and prioritize high-impact AI agent use cases. They are responsible for designing, building, and deploying production-ready AI agents using the enterprise stack while ensuring alignment with security and governance standards.
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