apache-airflow jobs in San Diego

Senior Snowflake Forward Deployed Engineer who builds AI-enabled solutions and agentic platforms for enterprise clients, with 7+ years of software/data engineering experience and 1+ years of hands-on GenAI/LLM deployment. Will design and deliver production-quality code using strong testing, CI/CD, and documentation practices, lead project workstreams translating business problems into AI solutions, and mentor other engineers through design reviews and reusable component contributions.…See more Must hold or be able to obtain a US government security clearance and have current SnowPro Core Certification, with hands-on experience in Snowflake Cortex AI, LLM Functions, Agents, or Arctic Embed.

Build and ship agent-based AI verification workflows from proof-of-concept to production, designing test cases for non-deterministic agent behavior and hardening code for quality, observability, and cost. Own your slice of the SDLC—implementation, testing, deployment—while building data ingestion pipelines on AWS and collaborating with Product and senior engineers to translate business requirements into features.…See more Requires 2–4 years of software engineering experience, strong Python or backend language skills, SQL/NoSQL knowledge, and hands-on experience building LLM-based projects that call tools, chain steps, or coordinate multiple operations.

Build and ship agentic AI capabilities (e.g., Vertex AI-based Discovery Agents) from design through production, owning the full software development lifecycle, implementation, testing, and deployment. Harden proof-of-concept agent code into production-grade quality with strong error handling, observability, and testing.…See more Design test cases and evaluation checks for non-deterministic agent behavior, and build data ingestion pipelines using AWS and big-data tooling. Contribute to production support including monitoring, alerting, and incident response for an AI-driven service.

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.

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).

Senior AI Engineer role focused on designing and leading scalable, high-performance data architecture solutions that support AI/GenAI use cases. The role involves building and optimizing data pipelines, defining database schemas (Graph, SQL, NoSQL), and leading infrastructure for AI model deployment across cloud and on-premises environments.…See more Requires 4+ years in data engineering/MLOps with hands-on AWS/Azure/GCP experience, 2+ years managing technical teams, and expertise in DevOps, CI/CD, containerization (Kubernetes, Docker), and ML deployment frameworks. The position includes mentoring junior engineers and driving technology modernization initiatives.

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.

Senior Data Engineer responsible for designing, developing, and operationalizing scalable healthcare data platforms and integration pipelines across claims, payments, member, provider, eligibility, medical, and pharmacy domains. The role requires 10+ years of consulting experience with 6+ years in healthcare and Medicare business knowledge.…See more You will deliver cloud-based data products using Azure Databricks, PySpark, Python, AWS services, Teradata Vantage, Informatica, Airflow, GitHub, and Azure DevOps, while leading technical initiatives and coordinating with stakeholders.

Principal Engineer Data will develop and execute a data architecture strategy aligned with business goals, building and maintaining data models, metadata standards, and integration frameworks. The role requires leading technical assessments for digitizing core business functions, working with stakeholders to translate requirements into architectural solutions, and ensuring data storage, retrieval, and governance meet enterprise standards.…See more The candidate must have a STEM degree with at least 5 years of experience (or Master's with 3 years), strong expertise in SQL Server, data visualization tools (Tableau, Power BI), and data architecture principles including data integration, governance, and security protocols.

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.

Staff Engineer who will design, build, and operate the Forge Platform—a distributed-systems foundation serving autonomy, ML Ops, simulation, and application teams. You will own architecture and technical standards for workflow orchestration, asynchronous processing, event-driven systems, and long-running service workflows while remaining hands-on in implementation, production troubleshooting, and reliability improvement.…See more Required: strong production experience with distributed systems, cloud-native platforms, or backend infrastructure; fluency in Go and Python; deep understanding of failure handling, consistency, fault tolerance, and state management; and ability to turn recurring infrastructure needs into reusable platform capabilities. You will work across Kubernetes, service networking, observability, and data pipelines to enable downstream teams to move faster on mission-critical systems.

Build, deploy, and continuously improve MITRE ATT&CK–aligned threat detections across cloud, endpoint, identity, email, and application telemetry. Own the full detection lifecycle from hypothesis and data validation through deployment, tuning, and retirement, advancing a detection-as-code platform with version control, peer review, automated testing, and CI/CD.…See more Evaluate AI-powered security capabilities including LLMs, anomaly detection, and response automation. Partner with Security Operations on investigations, incidents, and detection maintenance.

Staff Engineer responsible for designing, building, and operating the Forge Platform—a distributed-systems foundation serving autonomy, ML, simulation, and test teams. You will architect cloud-native backend infrastructure, establish reusable platform capabilities, define technical standards, and remain hands-on in production troubleshooting, performance analysis, and reliability improvement.…See more Required: deep expertise in production distributed systems, Go and Python, workflow orchestration, and the ability to translate complex architecture into usable interfaces across multiple downstream teams.

Lead hands-on modernization of legacy SSIS/SSRS ETL workloads into cloud-native Lakehouse pipelines using Databricks, dbt, Fivetran, and Airflow. Design and enforce standardized data frameworks (ingestion, transformation, curation, consumption), drive CI/CD and observability practices, and mentor engineers on modern data engineering patterns.…See more Evaluate emerging technologies (Delta Live Tables, Iceberg, streaming, AI-driven observability) through POCs and POVs, and leverage AI-assisted tools (Databricks Assistant, GitHub Copilot, Cursor AI) to accelerate development and reduce technical debt. Optimize Spark workloads and orchestration across Azure and GCP environments while partnering with architects, platform engineers, and business stakeholders.

The Data Architect will design and oversee enterprise data platforms, databases, and integration pipelines across SQL, NoSQL, and cloud services. Responsibilities include establishing data standards, implementing governance frameworks, architecting ETL/ELT pipelines, managing database platforms, and enabling analytics and BI.…See more The role requires 12+ years of progressive experience with cloud data platforms (Snowflake, Azure SQL, MongoDB Atlas, Cosmos DB), advanced SQL and Python skills, and proven leadership guiding engineering teams on enterprise data strategy.

Build and deploy production-grade AI models that power Petco's e-commerce platform, including personalized recommendations, demand forecasting, and price optimization. Design and maintain robust MLOps pipelines for automated model retraining, monitoring, and 24/7 reliability across web and mobile.…See more Partner with Software Engineering and Mobile teams to integrate AI features into production systems, and mentor junior engineers on ML engineering best practices. Experiment with emerging technologies like Generative AI and LLMs to drive business impact.

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.

Senior Platform Engineer responsible for designing, building, and maintaining secure, scalable cloud infrastructure on AWS GovCloud to support AI/ML workloads and autonomous systems for DoD missions. Core duties include container orchestration (Kubernetes/OpenShift), Infrastructure as Code (Terraform/Ansible/CloudFormation), DevSecOps pipeline collaboration, and ensuring compliance with DoD cybersecurity standards and STIG requirements.…See more Requires 14+ years of cloud engineering, DevOps, or platform engineering experience with active TS clearance at start and ability to obtain TS/SCI. Will mentor junior engineers and partner with AI/ML teams to deploy advanced analytics platforms.

Senior Platform Engineer responsible for designing, building, and maintaining secure, scalable cloud infrastructure in AWS GovCloud to support AI/ML workloads and autonomous systems for DoD. You will manage container orchestration (Kubernetes, OpenShift), implement Infrastructure as Code (Terraform, Ansible, CloudFormation), ensure DoD cybersecurity and STIG compliance, optimize cloud resources, and collaborate with DevSecOps teams on deployment pipelines.…See more The role requires 9–14+ years of experience depending on degree, an active TS clearance at hire, and ability to obtain TS/SCI, with hands-on troubleshooting, mentorship of junior engineers, and technical documentation responsibilities.

Lead the modernization of legacy SSIS/SSRS data systems into cloud-native Lakehouse pipelines using Databricks, dbt, Fivetran, and Airflow. Design standardized frameworks for ingestion, transformation, and consumption layers while driving CI/CD, observability, and engineering best practices across Azure and GCP.…See more Evaluate emerging technologies (Delta Live Tables, Iceberg, streaming ingestion) through POCs and POVs, and leverage AI-assisted tools (Databricks Assistant, Cursor AI, GitHub Copilot) to accelerate development and reduce technical debt. Provide technical guidance to the team and translate business requirements into scalable data solutions.

Principal-level individual contributor role leading AI/ML architecture and engineering strategy at scale. Requires 13+ years across ML, data engineering, and distributed systems, with 3+ years shipping production Generative/Agentic AI systems.…See more Hands-on expertise in RAG, vector databases, LLM optimization, agentic orchestration, and MLOps/LLMOps practice. Will set technical direction, own architecture decisions, drive platform initiatives, and raise engineering standards across the organization without direct people-management responsibility.

SAIC seeks a System Administrator for expeditionary systems integration, focusing on AI capabilities across sensor kits, unmanned systems, command-and-control, and TAK platforms. The role involves hands-on troubleshooting of network connectivity and OS updates on Linux edge servers, testing machine learning capabilities in field experiments, and collaborating with ML engineers and data engineers to integrate and monitor tactical data pipelines.…See more Responsibilities include building tactical systems for exercises, ensuring performant data flow between sensors and C2 systems, and working with software engineers to connect data infrastructure to operational systems. Required: 2+ years in system administration, data engineering, ML engineering, or related roles; intermediate Linux command-line proficiency; experience with edge servers, containerization (Docker/Kubernetes), and tactical system troubleshooting.