agentic-ai jobs in San Diego

Lead product strategy and roadmap for Intuit's next-generation Agentic AI Platform, designing core execution frameworks, agent libraries, and SDKs that enable complex reasoning and autonomous task execution across TurboTax, QuickBooks, Mailchimp, and Credit Karma. Define extensible platform architecture, drive multi-step planning and orchestration capabilities, and ensure agent observability and trust at scale.…See more Partner closely with engineering and architects to standardize agent development, deployment, and management while mentoring other product managers on technical fluency and platform thinking.

Lead the design and deployment of AI agents and automation tools across Intuit's talent acquisition function. You'll partner with TA teams to identify high-impact AI opportunities, build working prototypes using LLM APIs and agent frameworks, establish governance and performance metrics for deployed agents, and translate validated solutions into production requirements with engineering teams.…See more This role requires both deep TA domain expertise and hands-on AI implementation experience—you'll move from problem discovery through prototype validation to scaled deployment while maintaining human oversight and compliance.

The Cybersecurity Engineer II will design, engineer, and deploy cybersecurity and network defense solutions across complex DoD environments, with hands-on responsibility for SIEM, IDS/IPS, firewalls, and vulnerability management platforms. The role involves configuring Splunk Enterprise, conducting network and security analysis with tools like Wireshark and Tenable, and leveraging automation and APIs to improve security operations.…See more The engineer will support DoD Computer Network Defense requirements, integrate solutions across Windows, Linux, and network infrastructure, and collaborate with government and vendor teams throughout acquisition, testing, and deployment. The position requires 5–7+ years of hands-on cybersecurity and network defense experience, a Bachelor's degree in a related technical field, and an active U.S. national security clearance.

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.

This Cybersecurity Engineer II role involves designing, engineering, integrating, testing, and deploying cybersecurity and network defense solutions across complex DoD environments. The position requires planning and executing National Security and Cybersecurity assessments, configuring enterprise tools such as Splunk Enterprise, IDS/IPS, firewalls, and vulnerability management platforms, and conducting network and security analysis using tools like Wireshark and Tenable.…See more The engineer will leverage automation, scripting, APIs, and generative AI to improve cybersecurity operations while supporting the full acquisition, integration, deployment, and sustainment lifecycle for DoD Computer Network Defense requirements.

Founding Product Engineer to build a greenfield physical AI product at Netradyne, working across full-stack infrastructure, product UX, and agentic AI features. You'll design multi-tenant cloud and edge systems on AWS with real-time dashboards, compliance analytics, and AI-powered agent orchestration for safety operations.…See more Expected to own end-to-end problems—from device to cloud to customer—with 7+ years of software engineering across backend (Go, Python, Java), cloud infrastructure (containers, CI/CD, distributed systems), and modern frontend (TypeScript/JavaScript). Direct customer collaboration and rapid iteration in the field required; fluency with AI-assisted development tools (Claude, Cursor) expected.

Director-level role leading cyber architecture strategy and teams at an enterprise consulting firm. Responsibilities include architecting secure cloud and AI-enabled solutions, guiding security controls and design patterns, mentoring security professionals, and providing technical thought leadership on emerging technologies like generative AI and agentic systems.…See more Requires 10+ years of security architecture experience, expertise across IaaS/PaaS/SaaS platforms, and proven ability to influence enterprise technology strategy while balancing business enablement with risk management.

This role requires a senior technical architect with 15+ years of Integrated Eligibility System Architecture and cloud infrastructure expertise to design and govern end-to-end data center infrastructure across compute, storage, and networking. The architect will define standards and patterns, lead infrastructure modernization to AWS, and provide strategic guidance on scalable, secure, AI-enabled environments.…See more Deep knowledge of cloud-native engineering, Infrastructure as Code, DevOps, and compliance/security requirements is essential, with particular experience in agentic AI and serverless Integrated Eligibility systems preferred.

As a Senior Software Engineer focused on AI Tools, you will reauthor and optimize generative AI models (LLMs like Llama, Phi, Qwen, and multimodal models) for efficient execution on Qualcomm's on-device hardware. You'll translate hardware constraints into model-level transformations that preserve accuracy while enabling edge deployment, integrate inference acceleration techniques, and collaborate with compiler and quantization teams to move research prototypes into production.…See more The role requires deep implementation-level knowledge of generative AI architectures, strong Python proficiency in large typed codebases, and hands-on experience optimizing inference for resource-constrained environments.

Design, implement, integrate, and commercialize video software modules on Qualcomm SoCs, including user and kernel mode drivers for playback, streaming, camcorder, and DRM use cases. Develop and optimize video compression, streaming protocols, and Agentic AI frameworks on Linux platforms while meeting performance, latency, power, and stability requirements.…See more Work with hardware and systems engineers to integrate cutting-edge video technology on Snapdragon processors for mobile and AI inferencing platforms. Requires expertise in Linux kernel development (V4L2, device drivers), video compression standards (H.264/H.265/AV1), streaming protocols (HLS/HTTP/RTSP/DASH), and embedded systems debugging.

This Staff Engineer role owns and executes BD's product security lifecycle for FDA-regulated medical device dispensing systems and their cloud platforms. Key responsibilities include defining end-to-end security architecture, conducting threat modeling and risk assessments, implementing secure SDLC practices aligned to NIST/OWASP/BSIMM, managing SBOMs and vulnerability remediation, and ensuring regulatory compliance (IEC 62304, ISO 14971, FDA cybersecurity guidance).…See more The role requires 5+ years of cybersecurity experience with FDA Class I/II devices, hands-on expertise in embedded/cloud/application security, and the ability to balance security controls with usability while supporting FDA submissions.

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.

Lead a group of managers and 30+ engineers across Intuit's tax platform organization, owning the technical vision and roadmap for tax engines, runtime platforms, and Tax Prep APIs. Set technical direction, drive reliability and performance improvements, and embed AI/GenAI capabilities into the platform while maintaining compliance and correctness standards.…See more Manage, coach, and develop engineering managers; build talent systems including hiring, succession planning, and performance calibration. Partner cross-functionally with Product, Design, and AI leaders to shape strategy and resolve systemic friction points affecting tax prep quality.

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, implement, and optimize real-time embedded modem firmware across protocol layers and drivers while meeting strict latency, memory, and power constraints. Pioneer AI-native development practices by integrating AI coding agents, LLM-based code review, and automated test synthesis into daily workflows to accelerate delivery and debugging.…See more Own end-to-end feature delivery from requirements through on-target bring-up, and debug complex multi-layer hardware issues using AI-assisted analysis. Requires deep expertise in modern C/C++, embedded systems (DSP/Arm architectures), RTOS internals, data structures, and hands-on target hardware debugging, combined with practical experience using AI coding assistants and agentic tools.

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.

Senior Forward Deployed Engineer responsible for building and deploying GenAI/LLM-powered solutions on AWS, working directly with enterprise clients to translate business needs into production AI systems. The role requires 5+ years of software/data engineering experience, 1+ years hands-on with AWS AI&Data services (Bedrock, Neptune, OpenSearch), and the ability to lead technical workstreams while mentoring team members.…See more You will prototype solutions, develop scalable AI patterns with human-in-the-loop controls, write production-quality code with strong testing and CI/CD practices, and create reusable assets including code libraries and reference implementations. 50% travel required.

Forward Deployed Engineer who partners with enterprise clients to identify business needs and prototype production-grade GenAI/LLM solutions on AWS. Designs and builds AI-enabled agentic platforms, workflows, and scalable engineering patterns using AWS AI&Data services (Bedrock, Neptune, OpenSearch).…See more Delivers production-quality code with strong testing, CI/CD, logging, and documentation practices while mentoring team members and translating complex business problems into technical AI solutions.

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.

Conduct cutting-edge research in efficient generative AI, including LLMs, multi-modal foundation models, LLM reasoning, reinforcement learning, and agentic AI. Lead high-impact research initiatives and develop production-ready solutions with real-world commercial impact, with a focus on on-device deployment challenges.…See more Implement and evaluate solutions in both simulation and on-device environments, and publish findings in top-tier AI/ML conferences. Requires a Master's degree and 2+ years of experience (or PhD), with proven research excellence, deep expertise in generative AI and reinforcement learning, and hands-on experience with model development pipelines including training, fine-tuning, evaluation, and optimization.

As an Anthropic Forward Deployed Engineer, you will embed with government and public services clients to identify business needs and rapidly prototype GenAI-enabled solutions using Claude and related Anthropic technologies. You'll build production-quality AI solutions, agentic platforms, and workflows while working independently and collaborating with senior stakeholders to drive measurable business impact.…See more The role requires 4+ years of software/data engineering experience, 1+ years hands-on with GenAI/LLM solutions, and demonstrated expertise with Anthropic's platform technologies including Claude API, tool use, and extended thinking. You'll develop scalable AI patterns, contribute reusable assets, and mentor team members while balancing quality, safety, latency, and cost considerations.

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.