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Design and deploy AI-powered features that analyze voice and messaging data to improve customer conversations at scale using Python, ML frameworks, and cloud infrastructure.
AI Solution Engineer at MUFG Investor Services builds and evolves the Workflow and Agent AI Platform, owning AI-enabled features end to end across frontend, backend, AI, and integration layers, embedding AI agents into enterprise-grade systems. Core stack: TypeScript/React, Python, PostgreSQL, with cloud (AWS/Azure) and agent frameworks.
Senior AI/ML Engineer at Tempo (a Jira/Atlassian ecosystem productivity SaaS) shipping production AI systems for enterprise work management: LLM-powered insight synthesis, anomaly detection over event streams, a natural-language planning-rules compiler, evaluation frameworks, and MCP tool specs. Daily work spans Python (AI platform) and Kotlin/TypeScript (product platform), with AWS Bedrock + Clau
Lead engineer at a physician-led NYC fertility practice, owning the internal automation and agentic AI stack: building multi-agent LLM workflows, human-in-the-loop review tooling, and EHR (eIVF) integrations to automate tasks like insurance verification, chart prep, and lab triage. Core stack: Python/TypeScript, LangGraph, Temporal, PostgreSQL.
Architects and operates fleets of AI agents at BGBx, a pharmaceutical/life-science consulting and communications partner: designing multi-agent orchestration, agent routing, low-code workflows, and human-in-the-loop integrations over internal APIs, MCP/A2A, webhooks, and Slack. Salary €50,000–€70,000 per year.
Builder-leader role at DataZymes, an analytics/data science consulting firm: architect and ship production multi-agent LLM systems for pharma data pipelines, regulatory workflows, and document processing, while leading a small AI engineering team. Core stack: Python, agentic frameworks (LangGraph/LangChain/CrewAI), RAG, cloud platforms, Docker/Kubernetes.
Designs and builds AI agents and agentic workflows plus the backend services powering them — REST APIs and microservices in Python, Node.js, and PHP, with LLM integrations (OpenAI, Claude, Gemini, Azure OpenAI), MCP tool connections, database design, and dashboard/analytics backends. On-site in Noida; 6+ years' experience required.
Senior engineer on Sirion's Automation team builds and deploys agentic AI automations for contract lifecycle management: Python backend services (FastAPI/Flask/Django), LLM integrations (OpenAI/Anthropic/Gemini), agent frameworks like LangGraph/LangChain, RAG with vector databases, and Docker/CI-CD deployments with human-in-the-loop controls.
Senior AI Product Manager at DualEntry, a VC-backed startup building an AI-native ERP for accounting. Owns the Accounting Intelligence and AI platform end to end (agent framework, retrieval, evals), sets the roadmap, and works hands-on with engineers. On-site in NYC; $220k–$280k base plus equity.
Привет! Мы в Boiler Lab ищем джуна в команду партнёрств AIMLAPI — платформы, через которую разработчики подключают сотни AI-моделей по одному API. Опыт не обязателен. Важны английский B2+, интерес к AI-агентам и…
Solid Software seeks an AI Software Architect / Senior AI Engineer to design and run production-grade LLM systems — RAG, agentic workflows, tool calling, evaluation and observability — and integrate them with backend, mobile and web apps, deployed mainly on GCP. Requires strong Python and 5+ years shipping generative AI in production.
6-month end-of-studies internship in Sopra Steria's cybersecurity unit (Toulouse area) building AI-agent applications that analyze and validate security architecture dossiers. Day to day: prototyping autonomous agents (GPT, Gemini, Mistral) using LLMs, RAG and tool use to generate compliance matrices and automate architecture reviews. Python and JavaScript skills required.
A Google Cloud Forward Deployed Engineer embedded with strategic partners in Japan, building and shipping production-grade GenAI agentic applications (Gemini, Vertex AI) — coding, debugging, and solving integration/data/state challenges while feeding field insights back into Google's roadmap. Requires fluent Japanese and English.
Python AI engineer building generative-AI applications for enterprise clients: multi-agent architectures, RAG pipelines, and integrations with LLM provider APIs (OpenAI, Azure, Anthropic, Gemini, Bedrock). Requires 4-5 years of software experience and strong Python, working remotely with one day per week at the client's Milan office.
Client-facing forward-deployed engineer who designs, builds, and deploys end-to-end enterprise applications and AI-powered solutions directly with business stakeholders. Core stack: C#/.NET 8, Angular, SQL Server, Azure Databricks, plus Applied AI work with LLMs, prompt engineering, and RAG.
Designs, builds, and governs an enterprise-scale MCP server ecosystem connecting Claude/LLMs to business systems (SAP, Salesforce, D365, Jira) across a Bio-Tech/Healthcare portfolio. Day-to-day: schema design, production MCP servers in TypeScript/Python, OAuth/RBAC security, and multi-agent orchestration. Requires 8+ years experience and an IIT degree.
Senior engineer on NICE's new SPARK internal AI incubation team in Pune, designing and building enterprise AI tools end to end — LLM agents, RAG pipelines, and integrations with systems like Salesforce and Snowflake — from prototype through production handover, using Python/TypeScript, agent frameworks, and major cloud platforms.
Builds and deploys AI-driven agentic platforms for enterprise clients, integrating LLM frameworks like LangGraph and CrewAI with Python, Kubernetes, and enterprise systems.
Builds and deploys AI-driven agentic platforms for enterprise clients, integrating LLM agents with existing systems using Python, Kubernetes, and modern AI frameworks.
Proclink seeks an Agentic AI Architect (11-20 yrs) in Hyderabad, Ahmedabad, or Delhi/NCR to design end-to-end reference architectures for enterprise agentic AI systems — reasoning engines, planning, memory, and tool/API integration — using frameworks like LangChain, AutoGen, and CrewAI, while mentoring engineers and driving MLOps/LLMOps practices.
