openai jobs in San Diego

Design and build production AI systems integrated into enterprise workflows, owning the full stack from APIs and backend services through cloud infrastructure, data pipelines, and AI components. Lead multidisciplinary engineering teams, make architectural decisions across cloud platforms (AWS, Azure, GCP), containers, serverless, and infrastructure-as-code, while building agentic systems with tools, memory, and safety controls.…See more Own DevSecOps practices including CI/CD automation, security scanning, and incident response. Require 5+ years of production software engineering, full-stack development across multiple layers, hands-on experience with a major cloud platform, and proficiency in languages like Java, Python, Go, TypeScript, or C#.

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.

This role involves conducting comprehensive security assessments of AI systems and deployments, evaluating them against NIST frameworks (AI RMF, CSF, 800-53, 800-171) and other security standards. The consultant will identify AI-specific risks such as prompt injection, model misuse, data leakage, and supply-chain vulnerabilities across cloud platforms (AWS, Azure, hybrid).…See more Responsibilities include developing AI governance frameworks, policies, and controls; assessing AI development environments, model pipelines, APIs, and orchestration layers; and delivering executive-level recommendations and remediation roadmaps. Requires 7+ years of cybersecurity/consulting experience and 3+ years supporting AI/machine learning security initiatives, with strong expertise in AI threat modeling, secure AI deployment, and governance frameworks.

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.

Build and deploy production-ready AI solutions using LLM orchestration platforms (LangChain, LangGraph, CrewAI, n8n) and agentic workflows that integrate with existing data infrastructure like Snowflake. Develop sophisticated prompt engineering and RAG systems with vector databases, conduct independent data analysis to identify AI opportunities, and translate technical work into clear insights for leadership.…See more Move solutions from concept to deployed, maintainable tools with proper documentation and intuitive interfaces. Collaborate cross-functionally with data scientists, analysts, and stakeholders to drive organizational impact.

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.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

A senior DevSecOps engineer will design and operate an automated compliance and AI-driven security platform for DoD and federal healthcare environments. The role demands expertise in DISA STIG automation, container security, RMF/FedRAMP workflows, and SIEM/SOAR integration, with responsibilities spanning secure CI/CD pipeline development, Wazuh and Elastic Stack deployment, OpenRMF automation, and LLM-assisted security operations.…See more The engineer will build hardened base images, maintain compliance pipelines, develop Tines SOAR workflows, and mentor others on architecture decisions.

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.

Build and test agent behavior for an AI-driven service, including test case design and evaluation checks distinct from traditional software testing. Support data ingestion pipelines using AWS and BigData tools (PySpark, Airflow), collaborate with product and senior engineers to ship features, and contribute to production support (monitoring, alerting, incident response).…See more Requires 1–2 years of software engineering experience, a Master's in Computer Science or related field, proficiency in Python or another backend language, SQL/NoSQL fundamentals, basic REST API design, and hands-on experience with at least one LLM project (tool calling, chaining, retrieval, or multi-step coordination). Self-directed learner excited about AI tooling and focused on shipping end-to-end products.

Lead the design and engineering of enterprise-ready AI agents with retrieval, orchestration, policy-based routing, and lifecycle observability across multiple AI providers. Develop cloud-native abstraction layers, containerized microservices, and serverless architectures to deliver scalable agentic systems.…See more Tailor domain-specific workflows for finance, healthcare, and retail verticals through intelligent automation. Conduct design workshops, POCs, and code sessions with clients to shape data-driven agent workflows while defining metrics, evaluation harnesses, and best practices for agent accuracy, latency, safety, and cost-effectiveness.

Lead the design, governance, and technical implementation of an enterprise API and AI gateway platform serving internal and external consumers. Define solution standards, security controls, compliance protocols aligned to financial services regulations, and LLM integration patterns across Apigee X, MCP servers, and multiple AI providers.…See more Manage a team through API modernization and AI gateway buildout while actively contributing hands-on engineering on proxies, policies, and MCP integrations when needed.

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 Forward Deployed Engineer responsible for building and deploying production-grade AI solutions using frontier GenAI platforms (Claude, Gemini, GPT-4o) in client environments. Will lead end-to-end solution delivery, including architecture decisions, demo/POC development, and client enablement while mentoring junior engineers.…See more Requires 5+ years software/data engineering experience, 1+ years hands-on GenAI/LLM development, and demonstrated ability to translate business problems into scalable AI workflows with strong engineering practices (CI/CD, testing, documentation).

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.

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.

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.

Design and build production AI solutions including copilots, agents, RAG applications, and workflow automations on Azure OpenAI, Claude, and Microsoft platforms. Write custom code in Python, JavaScript/TypeScript, or C# and leverage low-code platforms like Power Automate and Logic Apps where appropriate, following solid engineering practices (version control, testing, CI/CD, AI output evaluation).…See more Integrate solutions with enterprise systems and APIs with security-first design, own projects end-to-end from deployment through adoption and improvement, and work with security, architecture, governance, and compliance teams to ensure production readiness. Communicate clearly to both technical and business audiences, document designs, and coach teammates on AI capabilities, limits, and risks.

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.

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.

As an Associate Software Engineer on the Digital Product Development team, you will participate in full-stack, full-cycle product development for cloud-native applications and IoT device lifecycle management platforms. You'll design, develop, and deploy web applications and services using languages like Java, React, and JavaScript, with emphasis on PaaS/IaaS, serverless services, and container technology.…See more Responsibilities include code reviews, CI/CD pipeline development, automated testing, and building reliable, scalable cloud-native applications following security best practices. The role requires solid technical acumen, strong problem-solving skills, and the ability to work collaboratively in a fast-paced, high-growth environment.

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.

Senior AI Software Developer who will design, implement, and integrate AI/LLM-enabled solutions and automation for Navy cybersecurity and mission workflows. You'll work in small, multidisciplinary teams translating mission requirements into technical approaches, delivering hands-on code (Python, APIs, data integration), and ensuring solutions align with RMF, security controls, and compliance boundaries.…See more The role blends advisory conversations with focused implementation of secure, deployable systems that reduce cyber risk and improve operational efficiency. Success requires 4+ years of software development or integration experience, Python proficiency, API and data store expertise, cloud or enterprise deployment knowledge, and ability to communicate across technical and non-technical stakeholders.