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Join a new squad building and maintaining production AI agents that support back-office operations for financial services. Day to day you develop agentic AI in Python (LangGraph, LangChain), design agent workflows, engineer and evaluate prompts, and deploy on Kubernetes.
An Applied AI Research Engineer at Anthropic probes new AI models to discover what they can do, builds demos and evals, and enables sales/field teams to deliver them, while going hands-on with strategic customers and feeding field learnings back into Product and Research. Core work centers on LLMs, evals, prototyping, and technical communication.
Founding AI engineer at Healf (hired via Uncover) in London building core platform infrastructure — identity, authentication, authorization — plus AI-powered agents and developer tooling for coding, QA, and incident workflows. Stack centers on Python, AWS, and agent frameworks like LangChain/LangGraph, with real architecture ownership and future team leadership.
AgileEngine is hiring a Senior AI Engineer (based in Buenos Aires, Argentina) to build AI-powered applications, AI agents, and MCP integrations that connect LLMs to enterprise tools. Day-to-day work uses Java and/or Python to turn LLM capabilities into production-grade backend services, covering prompt orchestration, tool calling, evaluation, and production support.
The Principal AI Software Engineer will design and deploy AI agents and advanced prompting systems to automate workflows and enhance client platforms. This role involves end-to-end development of AI-driven solutions, collaborating with cross-functional teams, and integrating AI capabilities into existing backend services and APIs.
The Senior AI Software Engineer will design and deploy full-stack, AI-enabled applications and distributed systems for clients. The role involves building intelligent agents, LLM-powered experiences, and data pipelines using modern cloud platforms and backend/frontend technologies.
Designs and delivers enterprise AI solutions using LLMs, agents, RAG, and cloud platforms; advises clients on AI strategy, governance, and implementation while building reusable AI frameworks.
Lead AI-driven business transformations for private-equity portfolio companies, designing strategies and roadmaps that turn AI into measurable revenue growth, cost savings, and enterprise value.
Twoday is hiring an AI Engineer to build and operate LLM-based applications, agents, and RAG solutions running on-premise for a Danish public-sector client in Aarhus. Day-to-day work centers on Python, self-hosted model deployment, and reliability engineering with guardrails, testing, and monitoring using Docker, Linux, APIs, and CI/CD.
Build production LLM-powered applications for fleet management, integrating natural language with enterprise data and cloud services using Python, Kotlin, and GCP.
Builds and owns Cobre's agentic customer-support layer end to end: an AI agent that resolves client questions against real systems (public API, Snowflake, Salesforce) across channels and escalates to humans when needed, with strict client-data isolation. Go-first AWS backend with LLM tooling like MCP servers and tool-calling agents.
Build and deploy AI-enabled enterprise solutions for financial clients, integrating Python, Azure, and Microsoft 365 with a focus on production-grade code and security.
Hands-on technical lead for Picnic's agentic grocery shopping assistant: owns architecture, model strategy and production code for multi-turn conversational agents, and builds evaluation, safety and observability patterns while mentoring engineers. Core stack includes Python, open-weight LLMs, RAG, fine-tuning and tools like PyTorch, LangGraph, vLLM, Pydantic AI, Qdrant and DeepEval.
Designs and deploys AI agents and workflows to automate business processes at a global sports platform company, using frontier LLMs and modern agent frameworks.
An AI Engineer (Engineer 3) designs, builds, secures, and maintains AI/ML and LLM solutions for the Department of Veterans Affairs Cybersecurity Operations Systems Engineering (COSE) program, working with cybersecurity engineers and government stakeholders to deliver production-ready, responsible AI capabilities.
Cognizant is hiring a GenAI Solutions Architect to lead AI-first engineering initiatives and design enterprise-scale generative AI solutions. Day to day, the architect collaborates with business leaders, product teams, and engineers to deliver scalable, cloud-native AI solutions on the AI & Digital Engineering team.
AI/LLM engineer at Traktorodetal, a federal heavy machinery and spare parts sales company, working on-site in Arkhangelsk (no remote). Day to day: identify AI automation opportunities, build and fine-tune ML/LLM solutions (chatbots, assistants, generation/classification), implement RAG and agentic workflows, and integrate them with corporate systems like Bitrix24.
Designs, develops and deploys GenAI solutions (LLMs, RAG, chatbots, intelligent automation) for Devoteam's clients, from POC to industrialization, working with data, cloud and product teams. Core stack: Python, LangChain/LlamaIndex, FastAPI, vector databases and cloud AI services like Azure OpenAI and AWS Bedrock.
Manages a team of software engineers on Google's Geo team (Maps, Earth, Street View, Maps Platform), setting technical roadmaps for generative AI work, reviewing code, overseeing system design, and coaching and developing engineers. Requires deep experience in ML/GenAI (LLMs, computer vision) plus technical and people leadership.
Leads and mentors a team of software engineers evolving the Gemini-based conversational dialog stack for Google Home, driving generative-AI work in natural language understanding, multi-modal inputs, response generation, and low-latency production LLM systems.
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