embeddings jobs in San Diego

Lead enterprise generative AI architecture and solution design on Oracle Cloud Infrastructure (OCI), focusing on agentic workflows, retrieval-augmented generation pipelines, and Oracle application integrations. Define governance, security, and compliance standards for AI/ML initiatives across the enterprise.…See more Mentor delivery teams on prompt engineering, model selection, and optimization; identify high-value AI use cases and guide pilot deployments that drive business outcomes.

This is a hands-on Solution Architect role for an AI-enabled Managed Services team, requiring deep technical expertise in designing end-to-end application architectures spanning UI, APIs, services, data, and AI components. The role combines hands-on coding and prototyping with architecture ownership, emphasizing active participation in codebases, AI tool evaluation, and guiding engineering teams through complex technical decisions.…See more Key responsibilities include designing reference architectures for AI patterns (RAG, vector search, prompt orchestration), defining non-functional requirements (performance, reliability, security), architecting CI/CD pipelines, and ensuring production readiness. The ideal candidate has 8+ years of software engineering experience, strong cloud-native and modern application architecture knowledge, practical AI feature development, and comfort working directly in code and infrastructure.

Design, build, and operate production-quality agentic AI systems and developer tooling at scale. Lead multi-agent orchestration, Model Context Protocol (MCP) integration, prompt engineering for structured output, and CI/CD automation for code review and testing.…See more Partner with engineering teams on discovery, rapidly prototype and validate capabilities, then own the full lifecycle from implementation through production monitoring. Mentor engineers on agentic design patterns and communicate technical tradeoffs to stakeholders.

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.

Lead end-to-end AI platform architecture and infrastructure at enterprise scale, designing and implementing generative AI capabilities including LLMs, RAG systems, and agentic AI with a focus on model serving, inference optimization, and production deployment. Establish MLOps/LLMOps best practices, build automated CI/CD pipelines tailored for AI/ML applications, and architect vector database integration and cloud AI/ML services.…See more Mentor engineering teams, drive cross-functional collaboration between software, product, and data teams, and continuously evaluate and optimize AI platform performance, scalability, and reliability.

Mid-level software engineer building AI/ML capabilities for a defense customer. You'll develop NLP and machine learning pipelines in Python (text analytics, topic modeling, embeddings, entity extraction), design knowledge graphs and network-analysis tools, develop collaborative TypeScript front-end applications, and deploy APIs and production systems.…See more Requires 4+ years Python development or equivalent front-end experience plus 2 years Python, hands-on NLP/ML experience, and ability to work with limited supervision.

Sr. Engineer responsible for designing, building, and deploying production-grade AI platforms and solutions centered on LLMs, RAG, and agentic workflows.…See more The role spans full-stack development—from backend services and APIs to cloud-native infrastructure on Kubernetes—with emphasis on enterprise search, retrieval optimization, and AI application integration. Must have strong programming skills across Python, Java, C#/.NET, Rust, TypeScript/JavaScript, and proven experience architecting and operating scalable, production-ready AI systems.

Design, implement, and troubleshoot AI/LLM-enabled software solutions for Navy cyber missions, including scripts, services, APIs, and automation workflows. Integrate systems across REST/HTTP APIs, relational and NoSQL data stores, and cloud or enterprise environments while respecting RMF controls and secure engineering practices.…See more Translate mission and security requirements into concrete technical tasks, deliver hands-on code in Python, and communicate trade-offs to both technical and non-technical stakeholders. Work in small Agile teams using Git and code review practices, with mentorship to reduce cyber risk across fleet and ashore enterprise.

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.

The AI Engineer designs, builds, and operates production-grade AI solutions in Azure Government (GCCH) environments, with a focus on LLM and RAG implementations. Responsibilities include testing and optimizing LLMs and model variants, benchmarking RAG systems, building MCP server integrations to connect AI agents to enterprise data, implementing agentic AI workflows using platforms like N8N and Copilot Studio, and developing modular AI microservices.…See more The role also involves supporting security practices (RBAC, Key Vault, data protection), monitoring and incident response for AI workloads, and helping BI and DevOps teams adopt AI capabilities toward production. A Bachelor's degree in Computer Science or related field and 1–2 years' experience with LLMs, RAG, or AI solution development are required.

The AI Engineer designs, builds, and operates production-grade AI solutions in Azure Government environments, focusing on LLM and RAG implementations, agentic AI workflows, and secure enterprise integrations. Responsibilities include testing and optimizing language models, benchmarking RAG systems, building MCP server integrations, implementing multi-step AI agents using platforms like N8N and Copilot Studio, and developing modular AI microservices.…See more The role requires hands-on support for security (RBAC, Key Vault, data protection), monitoring, and incident response in Azure Gov, with a focus on moving proofs of concept toward production deployment.

The Enterprise AI FinOps Lead establishes financial governance for company-wide AI usage across multi-cloud (Azure, AWS, GCP), SaaS, and on-premise environments. The role owns cost visibility, show-back, optimization, budgeting, forecasting, and stakeholder engagement, with deep responsibility for AI-specific cost drivers such as tokens, models, prompts, embeddings, and RAG systems.…See more The leader translates telemetry into actionable insights, optimization programs, and executive reporting while managing the full departmental budget. This is a hands-on operator role requiring 8+ years in FinOps, cloud cost management, or enterprise finance, with strong analytical, stakeholder management, and executive communication skills.

Build practical generative AI applications as a Python backend engineer, combining LLMs, RAG, and agentic AI systems. You'll develop FastAPI/Flask services, integrate LangChain/LangGraph workflows, manage vector databases, and deploy on AWS.…See more The role requires hands-on Python backend skills, prompt engineering, API design, and the ability to debug and own full-stack AI-powered services from development through testing and deployment.

Design, build, and maintain secure enterprise data platforms supporting AI/ML workloads, with responsibility for database optimization, CI/CD automation, and DoD compliance. Mentor junior engineers and provide technical leadership on architecture decisions.…See more Implement security controls aligned with NIST 800-53, RMF, and DISA STIG standards throughout the platform lifecycle. Develop ETL/ELT pipelines, support data lakes and lakehouses, and evaluate emerging data technologies for mission fit.

As a Software Architect, you will design AI-first software development lifecycles and lead teams in building GenAI-integrated platforms. You'll architect solutions using prompt engineering, RAG, embeddings, and agentic AI while managing multi-developer environments where AI agents and engineers collaborate.…See more You'll own product architecture, prototype AI-driven solutions with modern DevOps and observability, and coach teams on AI-accelerated development practices. The role requires 6+ years of production software experience, hands-on use of agentic IDEs, proven GenAI integration delivery, and strong architecture expertise across APIs, microservices, cloud platforms, and CI/CD.

This role leads enterprise generative AI architecture and solution delivery on Oracle Cloud Infrastructure, designing agentic workflows, RAG pipelines, and LLM-based integrations with Oracle applications. The candidate will define AI governance and security standards, identify high-value use cases, mentor technical teams, and guide model selection and optimization.…See more Requirements include 8+ years of enterprise architecture experience with 2+ years in AI/ML/GenAI solution architecture, hands-on expertise with OCI services (Generative AI Service, Functions, API Gateway, Data Science, Autonomous Database, Integration Cloud), and proficiency in Python, SQL, and REST APIs.

Principal-level individual contributor role leading AI/ML architecture and engineering strategy at scale. Requires 13+ years across ML, data engineering, and distributed systems, with 3+ years shipping production Generative/Agentic AI systems.…See more Hands-on expertise in RAG, vector databases, LLM optimization, agentic orchestration, and MLOps/LLMOps practice. Will set technical direction, own architecture decisions, drive platform initiatives, and raise engineering standards across the organization without direct people-management responsibility.

As a Staff AI Engineer, you will lead the design and evolution of Teradata's enterprise AI platforms, owning architecture decisions for agentic AI, LLM systems, RAG pipelines, and vector stores. You will operate with high autonomy, partner with product and architecture leadership, and drive technical strategy across multiple engineering teams.…See more The role requires 8+ years building backend services, distributed systems, or data/AI platforms, with strong proficiency in Java, Go, or Python and deep expertise in distributed system design, cloud-native architectures, and production AI systems. You will also mentor senior engineers, establish engineering standards, and serve as a technical escalation point for complex system design and reliability challenges.

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 end-to-end AI platform architecture and design for generative AI solutions, including LLMs, RAG systems, and agentic AI. Build MLOps/LLMOps pipelines with automated CI/CD, model serving infrastructure, and vector database integration on enterprise cloud platforms.…See more Establish best practices, mentor engineering teams, and drive seamless AI application integration into production systems while optimizing for scalability, security, and performance.

A junior software developer role focused on designing, implementing, and integrating AI/LLM-enabled automation and analytics for Navy cybersecurity and mission workflows. You will participate in technical discussions with cybersecurity specialists and mission partners, contribute to solution architecture and tradeoff analysis, and deliver hands-on work including scripts, APIs, and AI-assisted workflows.…See more The role requires hands-on coding in Python, API integration (REST/HTTP), version control (Git), and the ability to communicate technical concepts to non-specialists while respecting RMF, security controls, and responsible AI practices in classified or controlled environments.

Senior AI Software Engineer responsible for designing, developing, and deploying LLM-powered applications and AI-assisted development workflows within a large-scale enterprise Linux environment (~6M+ LOC, primarily C/C++). Build high-performance GPU-based inference pipelines using vLLM and modern frameworks, develop agentic AI workflows with RAG and tool calling, and integrate LLMs with vector databases and enterprise systems into production.…See more Collaborate across software engineers, AI researchers, and platform teams to productionize AI services while optimizing for performance, latency, scalability, and operational efficiency. Requires 4+ years software development, strong Linux/Red Hat experience, advanced C/C++, Python, LLM/RAG expertise, and GitLab CI/CD workflows.

SHEIN is seeking a Senior Data Engineer to build and productionize GenAI/LLM solutions for data engineering workflows, including code assistance, metadata discovery, and knowledge access. The role focuses on developing RAG and agentic workflows, automating incident triage and log analysis, and integrating AI capabilities into internal developer tools and services.…See more You'll own scoped projects from problem definition through production support, requiring 3+ years of hands-on production experience with strong Python/SQL fundamentals, proven GenAI/LLM application development, and practical knowledge of databases, APIs, data pipelines, and distributed systems.

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.

Senior Data Engineer role focused on building and productionizing GenAI/LLM solutions for data engineering workflows. You will develop RAG and agentic workflows, automate incident triage and root-cause analysis, integrate AI capabilities into internal developer tools, and own projects from problem definition through production support.…See more Required: 3+ years of production systems experience, strong Python/SQL, hands-on GenAI/LLM application building, and software engineering fundamentals including testing, CI/CD, and monitoring.