prompt-engineering 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

Enterprise Applications Developer responsible for building and supporting integrations among Salesforce, SaaS platforms, cloud services, and external partners using REST APIs, web services, and event-driven patterns. Develop Salesforce enhancements using Apex, Lightning Web Components, Flow, and SOQL/SOSL.…See more Design and maintain data extraction, transformation, validation, and loading processes; build workflow automations; and assist with AI-enabled solutions. Troubleshoot application and integration issues, maintain technical documentation, and support compliance requirements (HIPAA, SOC 2 Type II, SOX).

Lead a team of Databricks engineers delivering GenAI and LLM solutions to government clients. You'll architect and deploy production-scale data platforms, mentor engineers, and translate business requirements into AI solutions using Databricks' full stack (Lakehouse, Agent Bricks, Model Serving, Genie, Apps).…See more Enforce strong data management, CI/CD, testing, and documentation practices while working across AWS, Azure, and Google Cloud environments.

Lead machine learning strategy and development for AppFolio's Leasing products, owning the ML roadmap and autonomous leasing agent architecture. Build evaluation frameworks, model quality infrastructure, and establish ML standards across the Leasing Engineering team while ensuring production-grade reliability, SLOs, and observability.…See more Translate research into shipped features by evaluating fine-tuning approaches, RAG patterns, and agentic systems; operate with production discipline on a SaaS platform serving real customer workflows.

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 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.

AI Architect role requires designing and delivering enterprise-scale AI/ML solutions on AWS, with 5–7 years of cloud experience and 2–3 years hands-on with LLMs, agentic frameworks, and AI/ML services. The position demands deep expertise in AWS AI services (Bedrock, SageMaker, Kendra), orchestration frameworks (LangChain, LangGraph), RAG pipelines, MLOps tooling, and responsible AI principles.…See more Candidates must architect scalable, cost-optimized solutions integrating AI with cloud infrastructure, data platforms, and microservices, and communicate complex technical concepts to executive and technical audiences.

Lead a Palantir Forward Deployed Engineering team for the Government & Public Services practice, guiding architecture of data pipelines powering GenAI use cases. You will contribute production-quality code, enforce strong data management and CI/CD practices, and translate business problems into AI solutions while working with federal/state/local government clients.…See more The role requires 10+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment, and 1+ years working with Palantir (Foundry, AIP, or Maven), with deep familiarity in AWS, Azure, and/or Google Cloud environments.

Staff Engineer role driving Generative AI transformation across embedded software and engineering infrastructure at Qualcomm. Responsible for executing GenAI workstreams—converting engineering use cases into production-ready AI-enabled workflows for code generation, review, debugging, test automation, and documentation.…See more Will build reusable agents, prompts, MCP integrations, and evaluation flows; partner with embedded, platform, and software teams to onboard and increase adoption of secure, measurable GenAI solutions. Requires 4+ years software engineering experience, 3+ years hands-on GenAI/LLM application development, and strong proficiency in Python, C, C++, or Go with embedded systems familiarity.

Lead a forward-deployed engineering pod (2–5 engineers) architecting and delivering LLM-enabled applications, copilots, and agentic workflows using enterprise AI platforms, particularly Microsoft Azure AI Foundry. Own end-to-end GenAI solution design—from RAG pipeline governance and prompt engineering to production deployment and quality evaluation—while mentoring junior engineers, enforcing delivery standards, and translating business problems into scalable AI systems.…See more Require 7+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment in production, and proven ability to lead technical workstreams in ambiguous, fast-paced client environments.

Lead Qualcomm's GenAI transformation for embedded and software engineering, building reusable AI agents, agentic workflows, and developer productivity tools that scale across teams. Partner with platform and engineering teams to establish secure AI practices, governance models, and metrics while serving as a technical thought leader who shapes the organization's transition to AI-native engineering workflows.…See more Requires Principal-level technical leadership with deep expertise in generative AI, LLM-based systems, and hands-on experience deploying GenAI solutions in complex engineering environments. Collaborate on code generation, code review, test automation, and release readiness use cases while driving measurable productivity and quality improvements.

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 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.

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.

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.

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.

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.