guardrails jobs in San Diego

As an AI Scientific Software Engineer, you will develop MARIE, an AI-powered scientific companion within the BIOVIA 3DEXPERIENCE platform for pharmaceutical, biotech, and fine-chemical industries. You will build knowledge integration systems, agentic AI frameworks with tool calling and reasoning loops, and implement AI safety guardrails and validation mechanisms.…See more The role requires strong Python and LLM expertise, hands-on experience with frameworks like LangChain and LangGraph, RAG systems, prompt engineering, and vector databases. You will work collaboratively across application development, QA, product, and technical teams using Agile practices.

As an AI Scientific Software Engineer, you will develop MARIE, an AI-powered scientific companion within the 3DEXPERIENCE platform, focusing on knowledge integration, agentic AI workflows, and AI safety. You'll build systems that connect scientific data sources, implement retrieval-augmented generation (RAG) and semantic search capabilities, orchestrate multi-step agentic workflows with tool calling and reasoning loops, and establish guardrails for AI reliability.…See more The role requires strong Python expertise, deep LLM fundamentals (tokens, temperature, context windows), hands-on experience with frameworks like LangChain and LangGraph, and the ability to design and optimize prompts for scientific reasoning tasks.

The AI Scientific Software Engineer will develop MARIE, an AI-powered scientific companion within BIOVIA's Pipeline Pilot platform, focusing on prompt engineering, agentic AI frameworks, and AI safety mechanisms. Responsibilities include designing and iterating on prompts for improved reasoning and factuality, building multi-step agentic workflows with tool calling and memory management, and implementing guardrails and validation systems.…See more The role requires a PhD in Life Sciences or Computer Science with 3+ years of software development experience, strong LLM fundamentals knowledge, hands-on experience with RAG systems and frameworks like LangChain/LangGraph, and familiarity with pharmaceutical and biotech workflows.

You will develop AI-powered scientific software for MARIE, an AI companion within BIOVIA's Pipeline Pilot platform serving pharmaceutical and biotech researchers. The role focuses on prompt engineering, agentic AI frameworks, and AI safety mechanisms—designing and optimizing LLM-based workflows for multi-step scientific tasks.…See more You'll implement RAG systems, semantic search, vector databases, and guardrails while collaborating across engineering, QA, product, and technical teams using Agile practices. The position requires a PhD in Life Sciences or Computer Science, 3+ years of software development, and hands-on experience with LLMs, agentic frameworks like LangChain, and prompt optimization.

Lead a full-stack engineering team building AI/ML products at Accenture's QuantAI practice, bridging research algorithms into production systems for trading, investment, and optimization use cases. You will manage engineers across frontend, backend, and ML infrastructure; define quality standards and evaluation frameworks; coach team members; and collaborate with quants and client teams to ship end-to-end products.…See more The role requires 5+ years of shipped software experience, 2+ years of hands-on full-stack depth (frontend, backend, databases, deployment, debugging), and ideally deep experience designing LLM/agentic systems or working in high-stakes decision-support domains.

As a Technical Manager, you will lead the architecture, engineering, and delivery of AWS-based cloud contact center and Generative AI solutions. You'll design scalable solutions using Amazon Connect, Lex, Bedrock, Lambda, and other AWS services, incorporating AI patterns like RAG and agent/tool calling.…See more You'll translate client requirements into technical architectures and integration designs, partnering with stakeholders from design through implementation, testing, deployment, and production support. This role requires 8+ years in technology consulting or cloud architecture, including 4+ years deploying production AWS solutions and designing cloud contact center platforms with Generative AI capabilities.

Design, build, and deploy production agentic AI solutions powered by Claude for enterprise clients, from proof-of-concept through production. Implement multi-agent systems that automate business processes, integrate with enterprise tools, and operate within defined autonomy and guardrails.…See more Modernize existing AI/ML platforms with generative AI capabilities including RAG and agent-based orchestration. Advise clients on generative AI adoption strategy, responsible AI practices, and model selection while partnering with technology, data, and business stakeholders to scope and deliver solutions.

Develop and deliver Contact Center as a Service (CCaaS) and Contact Center AI solutions for enterprise clients. Design AWS-based architectures using Amazon Connect, Lex, Bedrock, and other services, with hands-on configuration of NICE CXone, Five9, Genesys Cloud, and integrations to CRM and enterprise platforms.…See more Implement generative AI capabilities including RAG, conversational AI, and guardrails. Mentor junior team members, communicate technical concepts to stakeholders, and support delivery from architecture through production support.

As Product Success Technical Director for AI Adoption Engineering at ServiceNow, you will own escalation resolution and architecture consulting for the company's most complex agentic AI deployments. You'll diagnose and stabilize at-risk customer go-lives, design resilient agentic architectures (LLM integration, RAG, multi-agent orchestration, guardrails, governance), and serve as the technical authority for customer executives during high-stakes moments.…See more You'll mentor the team, codify reusable playbooks and reference architectures, and act as a strategic conduit between field escalations and Product/Engineering to turn hard-won patterns into scalable capability.

Design, build, test, and operate production ML and LLM-powered components for cybersecurity applications at scale. You will turn ambiguous requirements into working code, partner across product and security teams, and apply AI safety and guardrail practices.…See more The role requires solid software engineering fundamentals, hands-on experience building production ML/LLM applications (RAG, embeddings, agents), and the ability to take prototypes to reliable, maintainable systems. You'll work with distributed systems, cloud-native technologies, and graph/data plumbing while contributing to code reviews and raising team quality standards.

AppFolio is hiring a Staff Machine Learning Engineer to design, build, and operate their ML platform on AWS, supporting training, fine-tuning, inference, RAG, and cost optimization across the organization's AI initiatives. You'll partner with applied AI and research teams to productionize prototypes, maintain multi-provider LLM reliability (OpenAI, Google, Anthropic), and operate AI safety guardrails and authorization layers.…See more The role requires production-scale ML infrastructure experience on AWS (ECS, SageMaker, GPU fleets), deep knowledge of model serving and inference optimization, hands-on language model training, and demonstrated cost discipline across AI workloads.

Principal AI Platform Engineer leading enterprise AI infrastructure strategy and governance at the platform boundary. Responsible for implementing and maintaining Bedrock Guardrails and Microsoft Purview DLP controls, managing AI vendor relationships with Microsoft and AWS, producing governance artifacts and runbooks, and leading internal AI adoption through community building and enablement.…See more Requires 7–10 years of cloud/DevOps experience with hands-on production expertise in AWS Bedrock (Agents, Knowledge Bases, Guardrails) and Microsoft 365 Copilot deployment in enterprise environments, including data integration, RAG architecture, and AI security controls.

A Forward Deployed AI Engineer who builds and deploys production AI/ML and Generative AI applications, particularly agentic workflows and RAG systems integrated with enterprise data and business systems. The role requires 6+ years of software/ML/AI engineering experience, advanced Python proficiency, hands-on expertise with LLMs, modern GenAI frameworks (LangChain, LangGraph, LlamaIndex), and cloud platforms (Azure, AWS, GCP).…See more You'll own solutions from prototype through production, working directly with product and business stakeholders to identify where AI creates value, troubleshoot integration issues, and drive continuous improvement.

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.

Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers.…See more Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.

Build the foundational agentic AI layer for a materials-science platform, including multi-model provider abstraction, agent orchestration with stateful checkpoints, retrieval systems, prompt versioning, and comprehensive tracing and evaluation frameworks. You'll design agents that plan and reason over tool calls in production, implement human-in-the-loop safety gates, and ensure all LLM behavior remains auditable and cost-tracked across customers' secure environments.…See more The role demands deep production experience with agentic and LLM systems: async Python, structured outputs, memory and context management, multi-step workflow orchestration, and evaluation harnesses that catch regressions before deployment.