langsmith jobs in San Diego

Senior AI Systems Engineer responsible for designing and operating CI/CD/CV pipelines, MLOps infrastructure, and observability stacks for production AI workloads at scale. Must build governance frameworks for AI assets (model registries, experiment tracking, CVE scanning), implement cost attribution and FinOps controls (OpenCost/Kubecost), and own the full observability layer (metrics, logs, traces, OpenTelemetry).…See more Requires 8+ years of hands-on DevOps/MLOps/platform engineering with production experience operating inference systems (Ray Serve, vLLM, Triton, NIM) on GPUs, GitOps tooling, and observability platforms, with ability to bridge engineering, architecture, and leadership on runtime and cost tradeoffs.

Lead DevOps and MLOps engineering for AI workloads at scale, owning CI/CD/CV pipelines, model-serving infrastructure (Ray, vLLM, Triton, NIM on GPUs), and a full observability stack (Prometheus, Grafana, Loki, Tempo, OpenTelemetry). Design and operate governance systems for AI assets (MLflow, Artifactory, Harbor, Trivy), cost attribution (Apptio, OpenCost, Kubecost), and FinOps controls; ensure every AI workload is delivered repeatably, traced end-to-end, cost-bounded per tenant, and policy-compliant by default.…See more Requires 8+ years in DevOps/MLOps/platform engineering with hands-on production ownership of AI or high-throughput services, and deep expertise in model-serving frameworks and observability tooling.

Build production AI features and workflows powered by large language models, including retrieval-augmented generation (RAG), agentic orchestration, and tool/function calling integrations. You will design and implement scalable microservices in Python or Java that connect foundation model APIs to business data and internal systems, with responsibility for AI quality, evaluation, observability, and safe deployment on AWS.…See more Collaborate with cross-functional teams to prototype solutions, measure outcomes, and move proven capabilities into production while maintaining reliability, security, and auditability.

Senior Machine Learning Engineer to design and ship production voice and conversational AI agents within AppFolio's Realm-X platform. You will architect real-time, multi-turn agent pipelines that balance reasoning depth against latency, lead a small pod of ML and platform engineers, and define quality metrics and evaluation harnesses.…See more Required expertise includes shipped production experience with agent frameworks (LangChain, LangGraph), voice stacks (STT/TTS/Voice-to-Voice models), LLM reasoning and tool use, Twilio, AWS, expert Python with async and WebSocket streaming, and demonstrated team leadership.

Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.…See more Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.

Build production AI features and services using foundation model APIs, retrieval-augmented generation (RAG), and agentic workflows. You will implement scalable microservices in Python or Java, develop evaluation and quality frameworks for AI systems, and collaborate across teams to integrate AI capabilities into enterprise workflows.…See more The role requires hands-on applied AI experience, strong backend or platform engineering skills, and familiarity with vector databases, LLM orchestration tools, and cloud infrastructure.

Principal Machine Learning Engineer at AppFolio to architect and lead mission-critical AI systems across the Realm-X property management platform. You'll design advanced AI agentic systems combining reasoning, planning, and execution; establish ML platform primitives for end-to-end production workflows; and drive the transition toward autonomous property management using LLMs, fine-tuning, and reinforcement learning.…See more Requires 10+ years building software systems with deep expertise in traditional ML, deep learning, generative AI, LLM post-training (SFT, RLHF, DPO, RL), and production ML at scale—plus a Master's or Ph.D. in Computer Science or related field.