Top Tech Jobs & Startup Jobs in Los Angeles, CA

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

Lead the design, development, deployment, and governance of advanced analytics, machine learning, and AI solutions using large healthcare datasets. Responsibilities include data preparation, statistical and predictive modeling, model monitoring, explainability, visualization, stakeholder communication, and translating findings into clinical and operational improvements. The role also mentors data professionals, advises leaders, manages initiative priorities and risks, and promotes responsible AI and Agile practices.

Work on front-end and back-end web projects: create and redesign websites, build sitemaps and wireframes, collaborate with teams, and focus on UI/UX and performant back-end functionality.

Lead and deliver Workday implementations with a focus on integrations. Design, build, test, and deploy Workday Studio integrations using Core Connectors, PECI, EIBs, and XSLT. Collaborate with business and technical stakeholders and own end-to-end integration lifecycle from requirements through production deployment.

Internship role to design and implement automated testing using low-code/no-code platforms. Create, maintain, and run automated test cases, document and track defects, produce test plans and reports, improve test coverage, and communicate progress with clients and teams. Involves end-to-end responsibility from planning through deployment and incorporation of feedback.

Develop, deploy, and maintain InterSystems IRIS/Cache applications and complex HL7 interfaces (SDA, CCDA, JSON). Implement CQ Initiator/Responder workflows, support IRIS in Kubernetes (IKO), use adapters (SFTP, HL7, HTTP), troubleshoot integrations, and collaborate across teams.

Develops and deploys machine learning systems for high-stakes decisions in pricing, claims, underwriting, and predictive health. Responsibilities span problem framing, quantitative research, experimentation, causal inference, predictive modeling, multimodal and foundation model development, agent systems, production deployment, and ongoing iteration. The role requires strong mathematical and statistical foundations, Python fluency, and expertise in machine learning, statistics, econometrics, or causal inference.

Design and build robust backend services and secure APIs for finance and reader applications. Implement authentication, payments, subscriptions, and finance workflows. Design Postgres/Redis schemas, integrate with financial APIs (BSE Star MF, NSE) and DRM services, and ensure compliance-friendly data handling.

Design and implement enterprise data and lakehouse architectures for client data, cloud, and AI transformation initiatives. The role requires hands-on expertise with Databricks, Azure, GCP, Spark/PySpark, SQL, Unity Catalog, governance, Terraform, and CI/CD. Responsibilities include client-facing solution architecture, clear communication, and delivery of scalable analytics solutions. Databricks Champion status is mandatory, while DPP experience is preferred. Immediate or 30-day-or-less availability is preferred.

Build and ship P-1 AI’s core product platform for Archie, an AI engineering agent. Own end-to-end features spanning architecture, backend, frontend, deployment, and reliability. Collaborate with AI researchers, forward-deployed engineers, founders, and customers to rapidly prototype, launch, and refine product concepts. Establish advanced AI-assisted development practices and continuously improve engineering workflows, product quality, and delivery speed.