Jobs at Autonomize AI

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.

Program-manage multiple machine learning initiatives from scoping through production, coordinating Product, Engineering, Clinical, and Customer teams. Establish roadmaps, milestones, risk management, evaluation frameworks, and operating rhythms for LLM, RAG, clinical NLP, and MLOps programs. Review technical designs and experiments, promote model reliability and observability, and mentor ML engineers and data scientists while improving processes and delivery scale.

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 complex production incidents across application code, APIs, databases, data pipelines, and cloud infrastructure. Implement permanent code and configuration fixes, lead Sev-1/Sev-2 response and postmortems, build automation and observability tooling, improve runbooks, support releases, and mentor L2 engineers. The role operates during US Pacific business hours from Bengaluru and requires healthcare compliance awareness, strong troubleshooting, and customer-facing communication.

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.

Build and deploy full-stack solutions integrating Autonomize AI with healthcare EHR and claims systems. Develop user interfaces, APIs, workflow orchestrations, and applied machine learning configurations for customer use cases. Partner with customers to analyze business needs, define success criteria, prototype workflows, and launch production deployments within 60 days. Support SaaS and VPC deployments while communicating technical AI concepts to healthcare stakeholders.

Lead the full product portfolio for an AI-powered healthcare administration platform, including applications, workflows, agents, and platform capabilities. Define strategy, roadmap, prioritization, and platform architecture while partnering with engineering, clinical advisors, customers, sales, and marketing. Drive AI product quality, enterprise adoption, pipeline influence, pricing and packaging expansion, and product-engineering alignment. Build and lead a high-performing PM team and establish an evidence-based operating cadence, with a potential path to Chief Product Officer.

Lead the People function and partner with the CEO and executive team to scale organizational design, workforce planning, performance management, leadership development, culture, communications, compensation, compliance, and People operations. Build scalable systems, analytics, automation, and talent programs while coaching leaders and supporting rapid growth across distributed U.S. and India teams.

Lead Autonomize AI’s strategy, roadmap, architecture, and production execution. Build and mentor a high-performing AI organization, oversee machine learning and generative AI systems, establish standards for reliability and safety, and drive initiatives from experimentation through deployment. Partner with Product, Engineering, Clinical, Customer Success, and Operations teams to deliver trusted AI solutions for healthcare workflows. The role requires deep technical expertise, strong organizational leadership, customer focus, and the ability to operate effectively in a high-growth environment.