Top Tech Jobs & Startup Jobs in Los Angeles, CA

Leads development and sustainment of secure, scalable production software using AI coding agents. Designs agentic development environments, orchestrates parallel workflows, validates AI-generated code, and integrates LLM platforms and conversational voice technologies. Advances cloud-native engineering, testing, APIs, databases, automation, and compliance practices while mentoring engineers and influencing technical stakeholders.

Conduct penetration tests across infrastructure, networks, web and mobile applications, and cloud environments. Perform application and cloud security testing, simulate adversary techniques, develop custom security tools, document vulnerabilities, validate remediation, and support HIPAA, SOC 2, and PCI DSS compliance. Collaborate with engineering and product teams, track emerging threats, and contribute to purple-team exercises, tabletop events, and security training.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Leads healthcare revenue-cycle consulting engagements focused on mid-cycle medical coding. Assesses current-state processes, develops future-state workflows, translates requirements into implementation plans, provides coding guidance, designs training and change-management strategies, and establishes KPI and SLA monitoring. Partners with executives, operational teams, process engineers, and clients to optimize coding workflows using AI and implement sustainable process improvements.

Designs, builds, and evaluates agentic AI systems for healthcare workflows such as documentation, coding, denial management, and revenue cycle automation. Develops long-horizon agent behavior, evaluation frameworks, benchmarks, feedback loops, monitoring, and production safeguards. Partners with research, ML engineering, clinical, product, and engineering teams to prototype and deploy reliable, explainable, auditable AI systems using LLMs, machine learning, and agentic technologies.

Build and deploy scalable AI/ML systems for retrieval, ranking, categorization, triage, and generative AI across healthcare data. Own solutions end-to-end from problem framing and model selection through production deployment and optimization. Collaborate with software engineers, product managers, clinicians, and operations teams to translate complex business problems into explainable, maintainable systems with measurable outcomes.

Build and deliver AI-powered healthcare products using React, Node.js, Python, and modern full-stack technologies. Partner with customers, designers, researchers, and product teams to understand workflow needs, design intuitive AI experiences, and own features from ideation through deployment, optimization, and scaling. The role requires strong product instincts, end-to-end software engineering ownership, and experience building production-grade applications.

Build and scale AI-native healthcare products through full-stack applications, backend services, data pipelines, and AI systems. Design, test, deploy, and operate production-ready software, run A/B tests, automate manual workflows, and collaborate with product, operations, and AI/ML teams. The role requires end-to-end ownership of scalable, secure, reliable systems and features, with a focus on performance, data integrity, clean code, and measurable business outcomes.

Conduct applied AI research focused on explainability, reinforcement learning, retrieval-augmented generation, and long-context retrieval. Design, train, and evaluate machine learning models using large-scale healthcare data and distributed infrastructure. Build research prototypes and experimentation frameworks, validate measurable impact, and collaborate with ML Engineering, MLOps, and Product teams to transition innovations into production.

Build and operate scalable data pipelines, backend services, APIs, and infrastructure powering AI-driven healthcare applications. Design distributed data systems, ETL workflows, streaming platforms, and cloud-native architectures while partnering with AI, machine learning, and product teams. Own production reliability, observability, security, automation, and on-call support for business-critical systems.