Top Tech Jobs & Startup Jobs in Austin, TX

Own full-cycle recruiting for engineering and AI teams, including sourcing, pipeline development, interview coordination, candidate experience, feedback management, offer negotiation, and recruiting analytics. Partner with hiring managers and leadership to define hiring needs, build diverse technical talent pipelines, improve recruiting processes, and support employer branding and recruitment marketing in a high-growth startup environment.

Owns expansion and value creation across large healthcare payer and PBM accounts. Builds executive relationships, identifies high-value AI and workflow automation use cases, develops ROI-driven business cases, drives adoption and scaled deployments, and coordinates internal Product, Clinical, AI/ML, Customer Success, Growth, and Operations teams. Serves as a trusted advisor and subject matter expert on payer/PBM operations while translating customer insights into strategic growth and product priorities.

Lead product marketing for Autonomize AI’s healthcare platform and solutions. Own positioning, messaging, portfolio taxonomy, naming, packaging, launches, competitive differentiation, sales enablement, customer evidence, and category leadership. Translate complex AI capabilities into business value for healthcare executives, support enterprise sales, monitor market trends, and drive analyst, media, and customer engagement to accelerate adoption, pipeline growth, and revenue impact.

Build and optimize production AI pipelines for healthcare workflows using LLMs, classical ML, VLMs, OCR, retrieval, agents, and fine-tuned models. Develop document extraction systems, evaluation harnesses, monitoring, and inference orchestration. Improve model quality, latency, cost, explainability, and safety while collaborating with product, engineering, senior ML engineers, and healthcare domain experts.

Own discovery and requirements for AI-powered healthcare solutions, translating payer and provider workflows into product specifications, process maps, data models, and scalable processes. Define KPIs, analyze healthcare data, support ML evaluation, validate data quality, manage backlog readiness, lead UAT and releases, create playbooks, model ROI, and align customers, clinical teams, product, engineering, and executives.

Owns commercial growth and expansion across strategic enterprise healthcare accounts. Responsibilities include account mapping, pursuit planning, customer discovery, executive engagement, solution and value alignment, deal leadership, negotiation, forecasting, and cross-functional orchestration. The role is quota-carrying and focused on expanding initial AI deployments across workflows, business units, and geographies while building long-term customer partnerships.

Own the pre-sales technical cycle for AI solutions serving healthcare payers and providers. Responsibilities include customer discovery, solution architecture, technical demos, prototypes, multi-agent workflow development, pilot and go-live support, and translating customer insights into platform improvements. The role requires strong programming, healthcare workflow expertise, LLM and multi-agent application experience, and effective communication with technical and executive stakeholders.

Leads and scales engineering for an enterprise Agentic AI platform serving healthcare payers and providers. Owns technical strategy, architecture, infrastructure scalability, security, compliance, DevSecOps, release execution, cost optimization, and customer deployment readiness. Builds high-performing global teams, partners with Product, CTO, Sales, and Customer Operations, and delivers resilient AI products supporting clinical workflows, interoperability, analytics, and enterprise integrations.

Lead the development, fine-tuning, deployment, and optimization of machine learning solutions involving LLMs, vision models, and NLP for healthcare applications. Build production-grade models and pipelines, support scalable GPU and TPU training, validate performance and compliance, collaborate with healthcare and product teams, and mentor junior engineers. The role also requires documenting technical approaches and applying MLOps and LLMOps practices in regulated environments.

Lead technical discovery, solution architecture, integration strategy, and deployment of enterprise AI solutions for healthcare payer clients. Translate business needs into scalable architectures for claims, clinical review, risk adjustment, and related use cases. Guide cross-functional teams through pre-sales, proofs of concept, and implementations while ensuring interoperability, security, governance, and HIPAA compliance. Partner with product and engineering teams on customer-driven improvements and healthcare data integrations.