Responsible for creating practical, governed AI workflows and integrations across marketing and GTM systems (research, content assembly, campaign execution, launch readiness, knowledge management, and reporting). Works with cross-functional GTM teams to integrate tools, ensure governance and QA, drive adoption, and convert experiments into reusable operational systems.

Design and implement a high-performance, cross-platform endpoint AI/model delivery framework for the Falcon sensor; collaborate with data scientists, security researchers, and endpoint engineering; optimize resource utilization and define testing approaches. Hybrid role based in Toronto, Canada (remote until office opens). Canadian-based employment; candidates must be legally entitled to work in Canada.

Join the Foundry team to design, build, and operate MCP server platforms, agent orchestration layers, and internal AI-powered tools used by GTM teams. Requires 5+ years' professional software engineering experience with expert TypeScript/Node.js, strong Python, AWS deployment experience, and demonstrated experience integrating with LLM APIs and agent frameworks.

Join Pindrop's Fraud Research team to develop and deploy applied machine learning for fraud and scam detection across voice, IVR, behavioral and metadata signals. Responsibilities include building risk models and scoring systems, analyzing fraud patterns, supporting investigations, and moving research into production. Requires an advanced degree or equivalent and 3+ years' relevant experience, strong Python skills, and experience with ML frameworks such as PyTorch or TensorFlow. US-remote.

Hands-on Senior Engineering Manager role for Thunderbolt (open-source AI product) responsible for production-readiness, release discipline, code quality, and scaling engineering practices. Manage engineers and contractors, contribute to codebase, coordinate across product and technical leadership, and support enterprise-ready features (security, privacy, self-hosted deployments). Role is fully remote in the US; salary range listed at $215,000–$240,000 USD/year; visa sponsorship not provided.

Customer-facing role working with EDA/CAD developers, chip designers, equipment OEMs, and fabs to GPU-accelerate EDA and manufacturing workflows (place-and-route, simulation, DRC/LVS, verification, lithography), apply ML/DL for defect detection, metrology, and yield optimization, and collaborate with engineering and product teams to deliver trainings, demos, and technical guidance.

NVIDIA seeks a Senior Solutions Architect to work with CAE/CFD/FEA ISVs, simulation platforms, and industrial OEMs to accelerate solvers and engineering workflows using NVIDIA accelerated computing, Omniverse, and physics-ML. Requires MS/PhD or equivalent, 4+ years in computational engineering or solver development, and experience with GPU acceleration, numerical methods, Python/C/C++, HPC, and simulation tools.

Join Veeva as a Senior Software Engineer on a founding team building an AI-first enterprise SaaS platform. Responsibilities include full feature ownership, design and development in Python (production-level), deployment and production support, code review, and mentoring. Required: 5+ years software development experience, strong Python expertise, experience building scalable, high-volume cloud SaaS applications, and familiarity with tools such as FastAPI, Pydantic, and Git. Applicants must have unrestricted US work authorization. Salary range listed: $110,000–$270,000 (base).

Senior technical role requiring 9+ years of experience in machine learning and AI. Responsibilities include designing ML/AI architectures, translating business use cases into technical designs, reviewing and defining scalable/extensible solutions, conducting POCs, and guiding developers. Required skills include Python or R, Pandas/NumPy, SQL, deep learning frameworks (TensorFlow, PyTorch, JAX), scikit-learn, MLOps tools (MLflow, Kubeflow), Docker/Kubernetes, LLMs and prompt engineering, generative AI techniques (GANs, VAEs, RAG), multi-agent systems, cloud/big-data experience, and familiarity with AI ethics. Bachelor's or master's degree in computer science, IT, or related field.

Lead design and delivery of AI/ML solutions (NLP, machine vision, generative AI, LLMs), translate business requirements into technical architectures, define non-functional benchmarks, and guide implementation and deployments on cloud and big-data platforms. Requires 11+ years experience, strong Python/R and SQL skills, proficiency with deep learning frameworks (TensorFlow, PyTorch, JAX), MLOps tooling (MLflow, Kubeflow, Docker, Kubernetes), experience building AI agents/multi-agent systems, and familiarity with AI ethics and responsible AI.

Senior technical leadership role responsible for designing and delivering data science and ML solutions. Requires 11+ years of experience with predictive modeling, statistical and time-series analysis, optimization techniques (LP/IP, genetic algorithms, RL), NLP and generative AI (RAG, LangChain, Llama Index), Python/R and libraries (Pandas, NumPy, Scikit-learn), cloud deployment (GCP preferred; AWS/Azure), and MLOps practices. Responsibilities include translating business requirements into technical design, defining architectures and non-functional guidelines, conducting POCs, reviewing designs, and guiding developers.

Senior technical leader responsible for architecting and delivering AI-powered, user-facing applications built with Python and React. Responsibilities include designing scalable, secure backend platforms for LLM inference, RAG pipelines and agent orchestration; defining frontend and AI-native UX patterns; establishing standards for prompt design, model integration, evaluation and observability; driving GenAI platformization; and ensuring enterprise readiness (security, privacy, compliance). Requires strong system design, cloud (AWS/Azure/GCP) and distributed systems experience and 11+ years total experience. Bachelor’s or master’s degree in CS/IT or related field listed as qualification.

Role on NVIDIA's GPU Communications Libraries and Networking team building and co-designing next-generation data center platforms and communications software (e.g., NCCL, NVSHMEM, UCX). Responsibilities include identifying performance bottlenecks, designing and implementing communication technologies, building proofs-of-concept, running experiments, and using simulation for large GPU clusters. Requires M.S./Ph.D. or equivalent experience, 12+ years relevant experience, strong C/C++, parallel programming and communication runtime experience, deep knowledge of system and network architecture, and strong Linux skills. Locations include multiple US offices and remote; posted salary ranges between 224,000 USD and 431,250 USD per year (depending on level).

Coforge (Encora) is hiring a Mid AI Engineer based in Peru (remote). The role requires 5+ years in AI/automation/bots (and 3+ years in enterprise environments), hands-on experience with Copilot 365, Copilot Studio, GitHub Copilot, Azure AI Foundry and RAG, plus knowledge of REST APIs, event-driven architectures, Azure Functions/Logic Apps and Python or JavaScript. Responsibilities include designing and optimizing AI agents and conversational flows, defining prompting and governance standards, orchestrating LLM integrations, ensuring scalability, security and compliance, and leading measurement and adoption of AI solutions in production.

Coforge busca un Fullstack Semi Senior con enfoque en Inteligencia Artificial Generativa para desarrollar agentes, copilotos y aplicaciones end-to-end en GCP (Vertex AI, Gemini, Cloud Run). Requiere 3–5 años de experiencia en producción, dominio de Python y React/TypeScript, experiencia con BigQuery, Docker, RAG y prácticas de seguridad y testing.

ActiveCampaign seeks a Senior AI Engineer for the AI Transformation Hub to architect and operate core platform capabilities for AI agents. The role focuses on deployment patterns, integrations, observability, shared services, and working with cross-functional teams to move agents into production. Requires 5+ years of hands-on engineering experience and practical experience with AI/LLM-based applications and cloud deployment patterns.

Nagarro seeks a Python developer to design, develop and deploy AI-powered applications focusing on Generative AI and Agentic AI. Responsibilities include integrating LLMs and AI services, building autonomous agent workflows, implementing retrieval pipelines and prompts, and ensuring performance, scalability and reliability. Desired experience includes Python, LLM-based application development, agent frameworks (LangChain/LangGraph/CrewAI/AutoGen or similar), prompt engineering, RAG, vector databases and familiarity with Elasticsearch, cloud platforms, containerization and MLOps practices.

Nagarro is hiring a Python developer to design, develop, and deploy Generative AI and Agentic AI applications. Responsibilities include building LLM-based solutions, orchestrating autonomous agents (using frameworks like LangChain, LangGraph, CrewAI, AutoGen), implementing RAG and retrieval pipelines, integrating with external APIs and enterprise systems, and optimizing for performance and scalability. Experience with Elasticsearch, vector databases, cloud platforms, containerization, and MLOps is noted as desirable.

Join a development team to design, build, and ship LLM-powered features in a large-scale production application. The role spans backend services, REST APIs (FastAPI), LLM systems (retrieval, RAG, agents, evaluation), and multi-agent production deployments. Candidates should have strong Python expertise, hands-on experience with major LLM model APIs (OpenAI, Anthropic), vector databases/semantic search, event-driven architectures, and daily use of AI-assisted/agentic coding tools.

Hands-on senior staff engineer role working with LLMs and agentic coding tools to build, refactor, and ship production generative solutions. Responsibilities include developing Python-based REST APIs (FastAPI), designing RAG systems (vector DBs, semantic search, chunking), using OpenAI/Anthropic APIs, building and securing MCP servers, implementing event-driven architectures and messaging, and applying prompt engineering, monitoring, and evaluation practices. Requires 2+ years with LLMs and 8+ years developing Python APIs.