• Build multi-step, tool-using agents that plan, retrieve, act, and verify. • Design agent architectures, integrate tools/APIs, and deliver robust execution with safety and observability. • Architect agent loops (planning, memory, retrieval, tool use, self-verification). • Implement tools (functions/APIs/DB queries/files) and MCP-style interfaces. • Combine RAG with agents: chunking, embeddings, retrieval, reranking, grounding. • Add guardrails: execution sandboxes, permissions, rate limits, PII policies. • Build evaluation for agents (task success, autonomy depth, recovery rate). • Optimize for reliability, determinism where needed, and cost.

• Design, develop, and maintain backend systems in Python, integrating AI-driven functionalities and APIs • Implement prompt engineering, Retrieval-Augmented Generation (RAGs), and basic generative AI solutions into platform workflows • Collaborate on AI model deployment, fine-tuning, and production integration • Apply ML algorithms such as linear regression, logistic regression, tree-based methods, and neural networks where applicable • Ensure scalable, secure architecture leveraging AWS services (EC2, S3, Lambda, etc.) • Contribute to architectural decisions, backend infrastructure, and system optimization • Work cross-functionally with product, data science, and engineering teams to align AI initiatives with business goals • Mentor junior AI engineers as the team grows • Stay current with emerging AI technologies and assess their applicability to product needs • Business travel necessary, especially for Remote candidates

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We're building a next-generation AI-powered platform and web application for creating audio and video content quickly and easily. This involves developing a revolutionary way to record, transcribe, edit, and mix audio and video on the web using state-of-the-art AI models—a challenge that requires solving complex technical problems. We're hiring a senior engineer to join our AI Platform and Enablement team. The ideal candidate thrives in a fast-moving, high-ownership environment and is comfortable navigating the ambiguity of bringing research work into an established product. The team’s objective is to support integrating cutting-edge first-party models (developed by our in-house AI Research team) and third-party/open source AI models into the Descript product. - Build, maintain, and standardize third-party model integrations, including consulting for other engineering teams with AI model integration needs - Design, implement, and maintain our AI infrastructure supporting our machine learning life cycle, including data ingestion pipelines, training developer experience and infrastructure, evaluation frameworks, and deployments / GPU infrastructure - Collaborate with Product Managers, Research Engineers, and AI Researchers to understand their infrastructure needs and ensure our AI systems are robust, scalable, and efficient - Optimize and scale our models and algorithms for efficient inference - Deploy, monitor, and manage AI models in production Qualifications - Experience in deploying and managing AI models in production - Experience with the tools of large volume data pipelines like spark, flume, dask, etc. - Familiarity with cloud platforms (AWS, Google Cloud, Azure) and container technologies (Docker, Kubernetes) - Knowledge of DevOps and MLOps best practices - Strong problem-solving abilities and excellent communication skills Requirements - Experience with generative AI models - Familiarity with audio and video processing - Knowledge of Python, C/C++, CUDA, and experience profiling GPU performance and distributed training runs - Experience with machine learning frameworks like PyTorch, TensorFlow or similar Benefits - A generous healthcare package - 401k matching program - Catered lunches - Flexible vacation time Company Description Descript is building a simple, intuitive, fully-powered editing tool for video and audio — an editing tool built for the age of AI. We are a team of 150 and the backing of some of the world's greatest investors (OpenAI, Andreessen Horowitz, Redpoint Ventures, Spark Capital). Descript is the special company that's in possession of both product market fit and the raw materials (passionate user community, great product, large market) for growth, but is still early enough that each new employee has a measurable influence on the direction of the company. Our headquarters are located in the Mission District of San Francisco, CA. We're hiring for a mix of remote roles and hybrid roles. For those who are remote, we have a handful of opportunities throughout the year for in-person collaboration. For our hybrid roles, we're flexible, and you're an adult—we don't expect or mandate that you're in the office every day. We do believe there are valuable and serendipitous moments of discovery and collaboration that come from working together in person. Descript is an equal opportunity workplace—we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We believe in actively building a team rich in diverse backgrounds, experiences, and opinions to better allow our employees, products, and community to thrive.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We’re looking for a Forward Deployed AI Architect to lead our most mission-critical client engagements. This is not a lab role - you’ll be embedded with enterprise clients, building and deploying AI solutions where the problems are messy, the stakes are high, and the environment is rarely “ideal.” You’ll be the one who makes things work in the real world: taking designs from architects, wrestling them into production, and ensuring they scale reliably under real constraints. If you thrive on chaos, love solving problems end-to-end, and want your code to matter outside of demos, this role is for you. Key Responsibilities - Client Engagement & Delivery: - Work side by side with clients, PMs, and Architects to scope and deploy AI systems that actually solve problems. - Build and integrate systems using LLMs, RAG pipelines, agent frameworks, vector DBs, and related tools. - Navigate real-world challenges: data access, authentication, security, networking, and brittle enterprise environments. - Solution Implementation: - Translate high-level designs into working components that deliver measurable outcomes. - Debug relentlessly - optimize for reliability in production, not just elegance in code. - Write modular, reusable code that balances speed of delivery with long-term maintainability. - Collaboration & Enablement: - Embed with client engineering teams to accelerate adoption and integration. - Share insights from field implementations to inform reusable components in our platform. - Document decisions with clarity so both clients and internal teams can build on your work. Qualifications - 5+ years of engineering experience, with proven work shipping AI/ML systems into production. - Strong Python skills and deep familiarity with modern AI/ML frameworks (LangChain, LlamaIndex, Hugging Face, vector DBs). - Hands-on with cloud deployment, orchestration, CI/CD, and distributed environments (AWS, Azure, GCP). - Ability to debug gnarly real-world issues (auth failures, networking black holes, flaky data pipelines). - Problem-solver who thrives in ambiguity, focused on delivery and reliability over process and ceremony. - Comfortable in client-facing environments - credible with engineers, clear with executives. Benefits - Impact: Ship AI systems that don’t just demo well but run at scale in Fortune 500 enterprises. - Growth: Stay hands-on with cutting-edge frameworks while developing field-tested instincts. - Variety: Solve problems across industries, from finance to healthcare to defense. - Culture: Work in a team that prizes resilience, creativity, and winning over process. - Trajectory: Build both your technical and consulting muscles in one of the most demanding roles in AI delivery.