vector-databases jobs in San Diego

Senior Developer role focused on developing new AI applications from concept to production within Dell's Office of the CTO. You'll work on small cross-functional teams using pair programming and agile methodologies, rotating through different projects and technologies across the full stack.…See more Required: strong programming fundamentals, proficiency in Go, Python, Java, JavaScript, C++, Bash, or similar languages, plus interest in DevOps practices (microservices, CI/CD, containerization), generative AI, and MLOps. Desired: 5+ years of software development experience, data engineering skills, and familiarity with GenAI frameworks like LangChain.

Director-level role leading AI/ML engineering strategy and execution across Optum's healthcare technology organization. You will define the roadmap for LLM engineering, generative AI systems, and agentic workflows; lead and mentor a team of 10+ AI/ML engineers, software developers, and MLOps specialists; architect scalable multi-cloud AI solutions spanning AWS and Azure with .NET/C# services; and champion ethical AI governance and production-grade model deployment practices.See more

Senior Enterprise Applications Developer responsible for designing, delivering, and supporting complex enterprise software, integrations, data solutions, and automation across cloud and on-premises environments. Requires 7+ years of progressive experience with advanced Python proficiency, hands-on expertise in REST APIs, ETL/data pipelines, CI/CD practices, and AWS or Azure cloud-native development.…See more Must demonstrate ability to lead solution design from requirements through production support, with experience in workflow automation, AI/LLM integrations, and compliance frameworks (HIPAA, SOC 2, SOX). Strong emphasis on security, governance, architecture, and cross-functional collaboration with technical teams and business leaders.

This Staff AI Engineer role focuses on architecting and implementing secure, scalable frameworks for autonomous AI agents at enterprise scale. You'll lead the technical roadmap for agent management—from discovery and provisioning through task orchestration—while ensuring safety, compliance, and governance by design.…See more Working cross-functionally with product, platform, and research teams, you'll build foundational infrastructure for multi-agent collaboration, memory management, and extensibility, driving adoption across the enterprise. The role requires 8+ years in software architecture, backend systems, and Kubernetes/AI infrastructure, with deep expertise in LLM frameworks (LangChain, AutoGen, CrewAI), cloud platforms (AWS, Azure, GCP), and identity/access control patterns.

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.

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.

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.

Senior AI Subject Matter Expert responsible for developing intelligent data processing and NLP pipelines, AI-enabled dashboards, and proofs-of-concept for AI use cases. The role requires 7+ years of professional experience with advanced expertise in LLM APIs, RAG architectures, agent-based development, generative AI coding tools, and secure AI deployment patterns.…See more Responsibilities include prototyping emerging AI developer tooling, mentoring engineering teams on generative AI workflows, and identifying software lifecycle areas that can be accelerated through AI and automation. The candidate must critically evaluate AI-generated code for correctness and security, understand AI-specific security risks across the full SDLC, and scope requirements for engineering solutions that meet business challenges with measurable outcomes.

Staff-level database engineer responsible for managing production database environments across MySQL, ClickHouse, and MongoDB at scale. The role demands independent execution, proactive monitoring, performance optimization through query tuning and indexing, and 24/7 on-call incident response.…See more Requires 4+ years of MySQL and cloud platform experience (Azure/AWS), strong Linux expertise, and scripting proficiency (Golang preferred); nice-to-have skills include AI tooling integration (LangChain, LlamaIndex), vector databases, and RAG for automating database operations.

Lead the design, development, and deployment of enterprise-scale Generative AI and LLM solutions across Azure and AWS environments. Define AI architecture frameworks, standards, and governance practices while architecting RAG systems, agentic AI, multi-agent systems, and vector database solutions.…See more Partner with business leaders and engineering teams to translate business requirements into scalable, secure, and responsible AI platforms. Mentor architects and data science teams while evaluating emerging AI technologies and driving innovation initiatives.

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.

Principal Engineer leading the technical direction for ServiceNow's Conversational Analytics platform, which enables customers to query data in natural language using AI. The role combines hands-on architecture and prototyping with mentorship of engineering teams, requiring deep expertise in AI/ML systems, vector retrieval, agentic architectures, and knowledge graphs.…See more You'll collaborate with product and leadership to design cloud-based solutions integrating LLMs and AI into enterprise workflows, with accountability for customer success metrics and evaluation frameworks.

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.

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.

Sr. AI Developer at XiFin will design and build AI-powered applications, agents, and automation tools that enhance software development workflows and improve engineering productivity.…See more The role involves developing intelligent testing solutions integrated with CI/CD pipelines, implementing AI-assisted developer tools using Claude and AWS Bedrock, and evaluating emerging AI technologies. You'll work hands-on across Python, LLMs, generative AI, and cloud-native AWS infrastructure, partnering with Engineering, QA, and DevOps teams to prototype and deploy scalable, production-ready solutions. The position requires 4–7+ years of software engineering experience with strong Python skills, LLM/generative AI application experience, and familiarity with modern DevOps practices.

Zensar is seeking an experienced AI Architect to design, develop, and deploy enterprise-scale AI and Generative AI solutions. The role requires deep expertise in Large Language Models (Claude, Gemini, OpenAI), multi-cloud platforms (Azure, AWS), and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years designing AI/ML solutions.…See more Responsibilities include defining AI strategy and architecture standards, designing end-to-end GenAI systems (RAG, agentic AI, multi-agent systems), architecting secure infrastructure across Azure and AWS, establishing governance and responsible AI frameworks, and leading adoption programs. The ideal candidate will mentor teams, evaluate emerging technologies, and translate business requirements into scalable, production-grade AI systems.

Lead the design and delivery of enterprise AI platforms and applications on Google Cloud, leveraging Vertex AI, Gemini, and cloud-native technologies. Design, fine-tune, and govern LLM solutions; build RAG and agentic systems; and define end-to-end architectures spanning data pipelines, feature engineering, model lifecycle, APIs, and MLOps/LLMOps.…See more Architect cloud-native applications on GKE, Cloud Run, and managed services while implementing security, governance, and production-grade monitoring for AI/ML systems at scale.

Design, develop, and optimize machine learning systems and models for production AI platforms, with focus on inference optimization, scalable ML infrastructure, and deployment. Responsibilities include building ML pipelines, optimizing model inference across hardware environments, integrating LLMs and models into APIs and microservices, designing data pipelines for ingestion and feature engineering, and collaborating cross-functionally on end-to-end ML solutions.…See more Requires strong software engineering fundamentals combined with deep ML expertise, proficiency in Python and at least one systems language (C++, Rust, or Go), and solid understanding of ML frameworks, transformer architectures, and model deployment systems.

Design, develop, and optimize machine learning systems for production AI platforms, including model development, inference optimization, and scalable ML infrastructure. Build training-to-deployment pipelines, optimize model serving for latency and cost, and integrate LLMs and generative AI models into microservices and APIs.…See more Develop data pipelines for ingestion, preprocessing, and feature engineering while collaborating cross-functionally with product, platform, and hardware teams to deliver end-to-end ML solutions.

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions.…See more Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

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.

Junior AI Software Developer supporting Navy cybersecurity and mission operations in San Diego. You will participate in problem discovery with mission stakeholders, contribute to technical solution design, and deliver hands-on implementation of scripts, APIs, automation, and AI/LLM-enabled workflows.…See more Work involves integrating systems via REST/HTTP APIs, writing and testing Python code, using version control, and documenting technical solutions for both technical and non-technical audiences while adhering to RMF, security controls, and responsible AI practices in classified or controlled environments.