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Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence . We work with…
Architects AI-powered GTM systems by defining low-code and custom agentic workflows (LangGraph, LangChain) for automation, integrating Salesforce/NetSuite, and setting enterprise-grade design standards for GTM engineering teams.
Senior ML/AI Engineer in NYC builds and deploys production-grade AI systems for demand forecasting, consumer intelligence, and autonomous decision-making using Python, ML frameworks, and graph RAG architectures.
Leads AI system architecture and engineering for an AI-native startup, designing scalable production-grade AI solutions and mentoring teams to deliver measurable business impact.
Builds and scales AI-powered fintech integrations at Plaid, focusing on backend APIs, LLM-driven features, and customer-facing AI agents to enhance financial data access and automation.
Build and maintain AI-driven financial data pipelines and forecasting systems using Python, Databricks, and LLMs to automate finance processes for a public IoT platform company.
Build and deploy generative AI tools for sales teams, including copilots, chat/voice interfaces, and personalized outreach, using Python, LangChain, and LLMs.
Build AI-powered HR tools and automations to streamline people operations, integrating systems like Workday and Salesforce using Python and LLMs.
Build and deploy generative AI solutions for healthcare, from prototypes to production systems, improving member experiences and operational efficiency.
Senior Product Manager at Lucid Software to lead AI-driven visual collaboration tools, building generative AI features and agentic workflows for teams using cutting-edge AI technologies.
Senior engineer building and deploying production-grade generative AI solutions for investment workflows, including retrieval pipelines, agents, and responsible-AI systems.
Develops and scales predictive modeling platforms (embedding-based sequence encoders, survival models, gradient-boosted decision trees) to identify vulnerabilities in housing, health, and social domains using ML pipelines, containerized systems, and responsible AI practices.
What You'll Do Avalara’s Customer Onboarding organization is scaling rapidly across professional services, managed support, assisted, guided, and self-serve implementation motions. We are seeking an AI Solutions…
Designs and deploys advanced AI/ML systems (LLMs, agentic workflows, multimodal models) for government/commercial clients, optimizing for production, edge, and security.
Principal Architect performing consultative discovery with clients to translate business goals into enterprise architectures, driving adoption of AI services (including agentic AI workflows) and cloud migration. Core technologies include AWS (Bedrock, Amazon Q), generative AI platforms (Claude, ChatGPT, Gemini), and agentic frameworks (LangGraph, CrewAI).
Builds AI-driven automation workflows using GenAI/Agentic tech to streamline fintech processes like onboarding, transactions, and reporting; integrates LLMs and RAG for context-aware decision support.
The AI Engineer will design, implement, and deploy LLM-based solutions into production to improve infrastructure and building design. The role involves end-to-end development of ML solutions, including data preparation, semantic extraction, and integration into a SaaS platform using Python and modern AI techniques.
Build and productionize AI-powered workflows and ML models for IT management and cybersecurity products, integrating classification, recommendations, and automation into Kaseya’s platform.
Designs and builds scalable, secure AI/ML platforms for healthcare, focusing on agentic systems, RAG pipelines, and multi-modal AI applications with guardrails and observability. Leads architectural standards, cloud-native infrastructure (Azure/AWS), and AI governance for enterprise-grade solutions.
Design and optimize agentic AI systems for healthcare workflows, focusing on retrieval, context, memory, and evaluation to ensure safe, transparent, and scalable performance.
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