model-monitoring 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.

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 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.

Staff-level front-end engineer responsible for building consumer-facing web and mobile applications using React, TypeScript, and JavaScript. Will lead a small team, mentor junior engineers, translate customer insights into mockups and proof-of-concept code, and drive AI integration into front-end solutions.…See more Requires 7+ years of web/mobile development experience, deep expertise in SDLC and software architecture, and demonstrated ability to build and deploy AI models in production.

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

Build and ship production ML systems end-to-end for autonomous medical coding in a SaaS platform, from problem framing through deployment and monitoring. Own the full lifecycle—data discovery, feature engineering, training, evaluation, and iteration—working with LLMs, deep learning, and modern MLOps tooling to handle millions of medical charts daily.…See more Design robust, low-latency architectures, establish rigorous evaluation strategies, and implement model observability, drift detection, and bias assessments. Collaborate across product, data, and platform teams to translate business goals into measurable ML outcomes.

A forward-deployed engineer who builds and deploys AI/GenAI-powered solutions on Databricks and cloud platforms for forensic discovery and financial crime clients. The role requires hands-on expertise in Databricks, cloud services (AWS/Azure/GCP), and production AI/LLM systems, combined with the ability to lead client engagements, translate business requirements into technical architectures, and troubleshoot integration issues across enterprise environments.…See more You will design reusable assets, document workflows, and enable client teams to sustain delivered solutions while navigating security, compliance, and privacy reviews.

Develop scalable AI engineering patterns and production-quality code for government clients, balancing quality, safety, latency, cost, and model risk. Apply strong practices in testing, CI/CD, logging, versioning, and documentation while designing extensible functionality aligned with senior team members.…See more Requires 4+ years of software/data engineering experience, 1+ year building and deploying GenAI or LLM solutions, and 1+ year with Google Cloud (Gemini API, Vertex AI Agent Builder, Grounding, or Google Workspace integration). Lead project workstreams, translate business problems into AI solutions, and contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

Design, build, and operate production ML systems across the full lifecycle—from data preparation and model training through deployment, monitoring, and continuous improvement. Partner with data scientists, software engineers, and platform teams to turn research prototypes into reliable, scalable services.…See more Work across recommendation, ranking, forecasting, classification, NLP, and generative AI depending on product priorities. Balance model quality, inference latency, scalability, and operational resilience as equally important outcomes.

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

Deloitte seeks a Forward Deployed Engineer to design, build, and deploy AI-enabled solutions and agentic platforms for government clients using Palantir technologies. The role requires hands-on experience building and operating GenAI/LLM-powered systems in production, contributing production-quality code with strong testing and CI/CD practices, and leading project workstreams to translate business problems into scalable AI solutions.…See more The engineer will prototype and deliver working solutions independently within a pod structure while mentoring teammates, balancing quality, safety, latency, cost, and model risk in architecture decisions.

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.

Senior Forward Deployed Engineer at Deloitte GPS building AI-enabled solutions and agentic platforms on Databricks for enterprise government clients. Requires 7+ years software/data engineering experience, 5+ years deploying GenAI/LLM solutions in production, and 5+ years hands-on Databricks expertise across Lakehouse, Agent Bricks, Model Serving, and Genie.…See more Mentors junior engineers, designs scalable AI patterns with human-in-the-loop controls, delivers production-quality code with strong CI/CD and testing practices, and translates complex business problems into deployable AI solutions.

Staff Analytics Engineer responsible for designing and operationalizing agentic AI workflows, ML models, and Databricks applications at scale. Will build multi-step agent pipelines combining rules, ML models, and reasoning to solve complex business problems, then productionize them with monitoring, drift detection, and retraining strategies.…See more Requires 5+ years of hands-on ML engineering or data science with production system ownership, deep Python proficiency, strong traditional ML foundations, and proven Databricks expertise including notebook apps, dashboards, and ML pipelines. Will serve as technical authority, mentor peers, and influence architectural decisions across teams.

Senior engineer at Deloitte GPS delivering production-quality code for GenAI/LLM-powered solutions, with 7+ years in software/data engineering and 1+ years hands-on experience building and deploying Claude-based applications. Responsibilities include designing extensible functionality, leading project workstreams, translating business problems into AI solutions, and contributing reusable assets (code, prompt libraries, runbooks).…See more Strong emphasis on testing, CI/CD, logging, documentation, and mentoring junior team members in fast-paced, ambiguous client delivery environments.

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.

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.

Staff Software Engineer leading front-end development at Intuit with 7+ years of experience building large-scale web and mobile applications. Responsibilities include architecting front-end solutions, translating customer insights into prototypes and production code, mentoring junior engineers, and integrating AI technologies into applications.…See more Requires expertise in JavaScript, TypeScript, React, REST/SOAP web services, TDD, and hands-on experience with AI integration, model monitoring, and performance optimization in production environments.

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.

Senior Microsoft Forward Deployed Engineer who will design, build, and deploy GenAI/LLM-powered solutions for government clients, translating business problems into production-grade AI systems. The role requires 7+ years of software/data engineering experience, 1+ years hands-on with GenAI/LLM solutions, and deep expertise in Microsoft Azure (AI Foundry, OpenAI, AI Search), Python/TypeScript/C#, and Copilot extensibility.…See more You will lead project workstreams, work directly with client technical teams in fast-paced environments, and mentor others while building reliable, maintainable, well-documented code. 50% travel required.

The AI Architect II is a senior technical leadership role responsible for establishing architectural standards and patterns for AI solutions, including RAG pipelines, agentic workflows, and model serving. The role involves designing scalable AWS cloud architectures, defining MLOps practices, implementing responsible AI governance, and translating business requirements into enterprise AI and cloud strategies.…See more The position requires hands-on technical expertise to evaluate and integrate AI/ML services, lead systems design across microservices and event-driven architectures, and mentor engineering teams on cloud and AI best practices. This role drives technology decisions with real business impact while modernizing the company's platform through cloud-native and AI transformation initiatives.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace.…See more Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.