generative-ai jobs in San Diego

Lead Forward Deployed Engineer responsible for architecting and delivering LLM-enabled applications (copilots, agentic workflows, assistants) using enterprise AI platforms like Claude, Gemini, or GPT-4o. Drive end-to-end RAG pipeline design, prompt engineering, evaluation frameworks, and data foundations while mentoring junior engineers and enforcing delivery standards across multi-pod engagements.…See more Require 7+ years software/data engineering experience, 1+ year hands-on GenAI/LLM production deployment, and proven ability to lead project workstreams and translate business problems into AI solutions.

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.

Senior Software Engineer role on the Core Infra Systems team, responsible for owning cross-cutting infrastructure initiatives across AWS, GCP, and networking pillars. You will build self-service tooling and paved-road defaults that enable product teams to provision and operate cloud infrastructure safely, drive standardization across Coinbase's multi-cloud environment, and embed security and compliance guardrails into infrastructure provisioning.…See more Requires 5+ years of software engineering with 3+ years building and operating production cloud infrastructure on AWS and/or GCP, hands-on experience with cloud networking primitives, proficiency in backend languages like Go or Python, and demonstrated ability to drive cross-team technical initiatives.

As an AI and Data Science Engineer III, you will translate business goals into machine learning use cases and develop predictive models for marketing and advertising applications. You'll perform exploratory data analysis, apply clustering and feature transformation techniques, build proofs of concept, and validate solutions.…See more The role requires 5+ years of industry experience applying data science or machine learning methods, with a strong foundation in translating business requirements into model design approaches and collaborating across analytics and data engineering teams.

Lead end-to-end technical architecture for complex PIM, PXM, and commerce SaaS implementations, translating business requirements into scalable solution architectures. Design data models, integration patterns, and system landscapes across PIM, DAM, ERP, and commerce platforms, with hands-on technical leadership to delivery teams on configuration, custom development, and integration.…See more Own technical integration strategy using APIs, services, and event-driven patterns; act as technical authority for risk identification and architectural decisions. Stay current on Agentic Commerce and GenAI trends to automate product content supply chains and drive AEO/GEO strategies for LLM syndication.

Lead system-level validation strategy, planning, and execution for next-generation premium mobile and AI accelerator SoCs at Qualcomm. Own end-to-end validation content across pre-silicon (emulation, FPGA) and post-silicon (silicon) phases, partnering with architecture, design, DV, firmware, and software teams to ensure comprehensive coverage.…See more Direct geographically distributed engineering teams, drive content quality and scalability, debug complex silicon and firmware issues, and champion AI/GenAI-driven validation methodologies. Requires 8+ years of SoC validation experience, deep knowledge of modern SoC architectures (ARM CPUs, DDR/HBM, NoC, power management, security), and proven technical leadership.

Join XiFin's Advanced Data Analytics team as an Associate Machine Learning Engineer to design, develop, and deploy machine learning models with a focus on LLMs, Generative AI, and Agentic AI in healthcare and revenue cycle domains. You will contribute to MLOps pipelines, perform data preparation and prompt engineering, collaborate with cross-functional teams, and validate models for production use.…See more The role requires a Bachelor's degree in Computer Science, Data Science, or related field, with proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and foundational knowledge of GenAI architectures, vector databases, and LLM orchestration frameworks.

Forward Deployed Engineer who embeds with clients to identify business needs and translate high-value GenAI use cases into production solutions. Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms, delivering production-quality code with strong testing, CI/CD, logging, and documentation practices.…See more Lead working sessions, prototype solutions, and mentor team members while balancing architecture decisions around quality, safety, latency, cost, and model risk. Requires 3+ years software/data engineering experience, 1+ years hands-on GenAI/LLM deployment, and 1+ years with Microsoft AI & Data (Azure AI Foundry).

A Technical Manager leading Google Gemini (GECX) implementations for enterprise customers, overseeing onshore and offshore delivery teams, managing client relationships with senior stakeholders, and driving business development. The role requires hands-on end-to-end delivery experience with GCP Gemini Enterprise for Customer Experience, including conversational agents (Dialogflow CX), Agent Assist, Quality AI, and contact center analytics platforms (BigQuery, Looker).…See more Responsibilities span project design, team building, best-practices advisory, quality assurance, proposal development, and staff mentoring across large-scale digital transformation engagements.

Senior forward-deployed engineer at Deloitte GPS responsible for developing scalable AI engineering patterns and production-quality GenAI/LLM solutions for government clients. Must have 7+ years software/data engineering experience, 1+ years hands-on with Palantir (Foundry, AIP, or Maven), and 1+ years building and deploying LLM-powered solutions in production.…See more Role emphasizes architecture balancing quality, safety, latency, cost, and model risk; delivering well-tested, documented code with strong CI/CD practices; and translating business problems into AI solutions while leading technical workstreams.

A forward-deployed engineer who embeds with enterprise clients to identify business needs and build production-grade AI solutions using Palantir platforms (Foundry, AIP, Maven). The role combines solution engineering—developing agentic AI systems, LLM-powered workflows, and scalable patterns with strong testing and CI/CD practices—with client engagement and stakeholder alignment.…See more Requires 3+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment, and 1+ years working with Palantir; involves 50% travel and mentoring of junior team members.

Enterprise Architect Director responsible for defining strategic architecture direction across core enterprise platforms (ERP, CRM, PLM, SCM, quality, laboratory, financial systems) and establishing enterprise-wide integration, API, data, cloud, security, and AI architecture standards. The role requires 12+ years of progressive IT experience with 8+ years in enterprise architecture, strong expertise in integration patterns, modern data platforms, public cloud (AWS/Azure), AI/generative AI, and proven leadership on complex portfolio rationalization and M&A programs.…See more This position influences executive leadership on technology strategy, manages architecture practice budgets and resources, and ensures compliance with GxP, 21 CFR Part 11, and GAMP 5 requirements.

Lead the scientific vision and execution of a generative AI platform for protein foundation models, starting with antibody and VHH design. You will build and manage a team of AI researchers and ML infrastructure engineers, define pretraining and post-training strategies across self-supervised learning, reinforcement learning, and transfer learning, and design confidence heads with out-of-distribution detection.…See more This is a founding role requiring deep expertise in structure-based generative modeling, multi-node GPU training, and the ability to shape cutting-edge computational approaches for therapeutic molecule discovery.

Senior Staff Technical Data Analyst responsible for data exploration, quality assessment, and governance across Finance Technology initiatives, including AI/ML pipelines and SOX-compliant financial reporting. Design and build end-to-end BI solutions using SQL, Python, Qlik, Databricks, and Tableau while identifying where GenAI and agentic approaches can modernize financial controls, anomaly detection, and self-service analytics.…See more Partner with Finance stakeholders (FP&A, Accounting, Revenue) to translate business requirements into technical solutions, and mentor junior analysts on craft standards for data quality and documentation. Requires 10+ years in data analytics or BI supporting Finance, Accounting, or regulated compliance functions, with proven expertise in cloud data platforms, data governance frameworks, SOX controls, and active hands-on experience with generative AI tools.

Design, develop, and optimize machine learning systems for production AI platforms, focusing on model development, inference optimization, and scalable ML infrastructure. Responsibilities include building ML pipelines and frameworks, optimizing model inference for latency and cost, integrating LLMs into APIs and microservices, and designing data pipelines for preprocessing and feature engineering.…See more The role requires strong software engineering fundamentals combined with deep ML expertise, working across PyTorch/TensorFlow, model-serving systems, distributed computing, and GPU environments.

Design, develop, and optimize production machine learning systems including model development, inference optimization, and scalable ML infrastructure. Build end-to-end ML pipelines from training through deployment, optimize model inference for latency and cost, integrate LLM/ML models into APIs and microservices, and engineer data pipelines for preprocessing and validation.…See more Requires strong software engineering fundamentals with deep ML expertise, proficiency in Python and systems languages, and experience with ML frameworks, model serving, and distributed computing.

This is a paid summer internship for undergraduates or graduate students to design, develop, and enhance automated test frameworks and AI-powered testing solutions for medical device software. The role involves developing automation scripts in languages like C#, Python, or Java; supporting AI agents and generative AI/ML technologies for test automation; executing test suites and analyzing results; and troubleshooting software, hardware, and integration issues across cross-functional teams.…See more Candidates should have at least 3 years of study in Computer Science, Software Engineering, or related fields, with hands-on experience in one or more programming languages and source control systems.

Senior Staff Engineer to develop end-to-end embedded AI software for deploying generative AI models on Qualcomm's edge AI accelerators. You will design and optimize ML/AI software stacks, kernels, and runtime software for power and memory efficiency, collaborate with hardware teams on new ML operators, and build debugging/profiling tools and SDKs.…See more Requires 6+ years of hardware, software, or systems engineering experience (or equivalent with advanced degree) and strong expertise in machine learning frameworks, neural network training/quantization, and languages like Python or C++.

Peraton seeks undergraduate and graduate software engineering co-ops to build and prototype software for San Diego County departments from January through August 2027. You'll write code using Python or Java, apply modern AI tools and AWS cloud services, and contribute to real projects modernizing public-sector services through rapid prototyping.…See more The role requires object-oriented programming experience and Git version control, with exposure to generative AI APIs, AWS services (Bedrock, CodeCommit, Lambda), and agile tools like JIRA considered valuable.

Join Amazon Private Brands' Selection Guidance team as a Data Scientist II to develop generative AI, machine learning, and statistical solutions for product assortment and business decisions. You will investigate business problems, invent novel solutions and prototypes, and guide other scientists on their designs and implementations.…See more Current research areas include named entity recognition, product substitutes, pricing optimization, agentic AI, and large language models. You'll partner with business stakeholders, perform data analysis and build pipelines, deploy production software, and publish research across Amazon.

As a Data Scientist II, you will partner with business stakeholders to frame and solve private brands product assortment and pricing problems using generative AI, machine learning, and statistical modeling. You'll investigate business problems using data, invent novel solutions and prototypes, and deploy production software while reviewing and guiding science solutions across the team.…See more The role requires strong expertise in data querying, machine learning, statistical modeling, and the ability to communicate complex concepts and publish research both internally and externally.

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.

Principal System Architect responsible for designing and maintaining a complex enterprise automation ecosystem spanning RPA, Machine Learning, and GenAI across multiple business units. The role requires architecting data pipelines integrating diverse systems (SAP, ERP, QMS, PLM tools like Windchill), leading automated workflow solutions (ECPs, QA defect prediction, EVMS reporting), and ensuring end-to-end cybersecurity compliance with DoD standards, CMMC, and Zero Trust architectures.…See more This is a senior technical leadership position requiring 14+ years of IT system architecture experience, deep expertise in intelligent automation and ML/AI, and the ability to mentor teams and present technical strategies to executive stakeholders.

Join Aphantic as a Software Engineer to design and develop web-based applications that integrate with custom embedded systems using AI-assisted coding tools. You'll write requirements and test documentation, execute testing, and interface with customers on requirements and design reviews.…See more The role requires 2+ years of professional software engineering experience, proficiency in Python, JavaScript/TypeScript, Go, C/C++, or Rust, Linux systems knowledge, and web-based UI development skills including TLS/HTTPS networking.

The AI Learning Architect designs and implements generative AI applications for learning and development, using prompt engineering, retrieval-augmented generation, and low-code automation to personalize training content and remove manual steps. They structure learning data into modular frameworks, evaluate and integrate AI tools with existing learning platforms, set up analytics tracking via xAPI, and debug prompt configurations to keep solutions accurate and current.…See more The role requires 3+ years in instructional design or educational technology with hands-on AI integration, proficiency in modern generative AI models and low-code tools, knowledge of learning frameworks (ADDIE, SAM), and the ability to translate technical AI behavior into accessible user experiences. They embed responsible AI practices including data privacy, bias checks, and accessibility from the start, while documenting workflows and coaching teammates.