Software Engineer, Agents & Automations
Design, build, ship, and maintain core capabilities for North’s Agents & Automations platform. Build product and platform features that help users create, run, debug, evaluate, and improve agents and automations. Own features end-to-end, from technical design through implementation, testing, launch, and iteration. Work across the stack, from frontend product surfaces to backend systems, depending on what the product needs. Make practical technical decisions that balance speed, quality, depth, and user impact. Collaborate closely with product, design, modelling, customer-facing teams, and other engineers to define the right outcomes and ship measurable improvements. Use AI actively in your work, while staying intellectually engaged and accountable for the quality and reliability of what you ship.
Research Intern, Inference (Fall 2026)
As an AI Infrastructure Engineer at Together, the responsibilities include participating in on-call rotation to respond to production incidents, building and running infrastructure using Ansible, Terraform, and Kubernetes to support scaling to a large number of concurrent users, building monitoring systems to ensure high-quality service, designing and implementing operational processes such as deployments and upgrades, debugging production issues across all services and stack levels, identifying improvements for product architecture in terms of reliability, performance, and availability, and planning the growth of Together AI's infrastructure.
Sr. Manager, Integrated Campaigns and ABX
Build and deploy AI Agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks. Act as the primary technical partner for customers by leading demos, communicating progress, gathering feedback, and guiding solutions from concept to production. Configure and connect systems using APIs, handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools. Set up telephony systems including SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality. Write and refine prompts for LLM-driven agents, monitor performance, and ensure agents meet automation and containment targets. Translate customer requirements into actionable solutions and work consultatively to unblock challenges in security, connectivity, or knowledge ingestion. Collaborate with product and engineering teams to address platform gaps and resolve technical issues, independently driving leading client implementations.
Senior Backend Engineer- AI Agents (Remote)
Design and build scalable backend systems powering AI Agents that operate in real-time enterprise environments. Develop agent orchestration frameworks involving multi-step reasoning, tool usage, and decisioning workflows. Build systems for agent memory, context management, and state persistence across interactions. Architect low-latency inference pipelines integrating Large Language Models, Small Language Models, and external tools/services. Implement evaluation frameworks to measure agent performance, accuracy, and reliability. Enable continuous improvement loops for AI agents in production including feedback, retraining, and deployment. Design and manage event-driven, asynchronous workflows for complex agent tasks. Optimize systems for high throughput, low latency, and cost-efficient inference at scale. Build and maintain robust APIs and service layers (REST/gRPC) for agent capabilities. Partner closely with Applied AI/ML teams to productionize models and agent behaviors. Collaborate with Product and Solutions teams to translate real customer workflows into agentic systems. Drive best practices in observability, monitoring, safety, and guardrails for AI systems. Contribute to architecture decisions for scaling multi-tenant, enterprise-grade AI platforms.
Member of Technical Staff (Machine Learning Engineer)
Translate cutting-edge research into production-ready machine learning systems. Design, build, and deploy end-to-end ML models and pipelines. Develop and optimize models for image and video processing. Own the full ML lifecycle including experimentation, training/fine-tuning, evaluation, and deployment. Rapidly prototype using open-source models and adapt them for product needs. Conduct experiments, analyze results, and iterate to improve performance. Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale. Participate with advancements in machine learning and apply them to continuously improve products.
Warehouse Supervisor (Temporary)
Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training. Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations. Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. Assist in designing and improving efficient annotation tools tailored for healthcare and administration data. Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance. Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.
Strategist, Agent Development (Dutch speaking)
As a member of the Agent Strategist function at Sierra, the role involves partnering with Agent Product Managers and Agent Engineers to scope, build, and ship AI agents that manage thousands of customer conversations daily. Responsibilities include being a trusted advisor to customers and driving their AI strategies, building, designing, and refining conversational AI agents while gaining direct exposure to their development and improvement. The strategist will drive execution and delivery of multiple complex, high-visibility agent development projects, coordinate across technical and non-technical stakeholders through the full development lifecycle, ensure clear communication and strong relationship-building among stakeholders, and contribute data-driven, strategic insights to both customers and internal team decisions.
Software Engineer, Agent (Dutch speaking)
Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, which are central and mission-critical to Sierra's growth across industries like finance, healthcare, and commerce. Take complete ownership and autonomy over the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices for ADLC. Partner with leaders at large enterprises and cutting-edge startups to understand their business challenges and build AI agents that transform their operations at scale. Collaborate with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and working with research, product, and platform teams to shape the future of AI agent development and Sierra's product.
Deployment Engineer
Translate business requirements into AI/ML model requirements. Prepare data to train and evaluate AI/ML/DL models. Build AI/ML/DL models using state-of-the-art algorithms, especially transformers, sometimes leveraging existing algorithms from research. Test and evaluate models, benchmark quality, and publish models, datasets, and evaluations. Deploy models in production by containerizing them. Work with customers and internal employees to refine model quality. Establish continuous learning pipelines for models with online or transfer learning. Build and deploy containerized applications on cloud or on-premise environments.
Lead Data Scientist
As a Lead Data Scientist, you will set the technical direction for complex, business-critical projects, balancing trade-offs between speed, innovation, and reliability. You will design and implement reliable, production-grade technical solutions and ensure comprehensive documentation of architectures and specifications. You will define project problems, develop clear roadmaps, and oversee end-to-end delivery across multi-disciplinary workstreams. Your responsibilities include leading technical scoping and feasibility studies for high-value sales opportunities and strategic customer engagements, managing relationships and communications with demanding clients to align technical solutions with shared long-term commercial goals, driving the adoption of best practices, shared resources, and robust technical processes across the wider Data Science craft, and mentoring and developing other data scientists and team members to contribute to the growth and technical excellence of the organization.
Access all 4,256 remote & onsite AI jobs.
Frequently Asked Questions
Need help with something? Here are our most frequently asked questions.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.