Job description

Senior Applied AI Engineer Role Summary We are hiring a Senior Applied AI Engineer to help us find and deliver practical AI solutions across the company. This is a hands-on role that covers the full life of a project — from sitting down with business teams to understand a problem, to deciding whether and how AI can help, to building the solution, getting it into production, and making sure people actually use it. You will split your time between business-facing work and engineering. Some weeks that means running discovery sessions and mapping how a process works today; other weeks it means writing code or configuring a platform. We care more about solving the problem well than about which tool you used to solve it. You should be comfortable starting from a vague problem rather than a written spec — asking good questions, defining what success looks like, and moving the work forward without waiting to be told what to do next. What You Will Do Work with the business • Meet with business teams to find and prioritize problems where AI can genuinely help, and be honest about where it can't. • Run discovery sessions: ask good questions, map how the work gets done today, and pin down the actual problem before proposing anything. • Define what success looks like for each project, including the measures you will use to show it worked. • Turn rough ideas into clear problem statements, options, and plans that both leaders and engineers can act on. Design and build • Design and build AI solutions such as copilots, agents, retrieval-augmented generation (RAG) applications, and workflow automations on the platforms we use today, including Azure OpenAI, Claude, and Microsoft Copilot. • Pick the right approach for each problem, whether that's custom code (Python, JavaScript/TypeScript, C#) or configuration on platforms like Power Automate or Logic Apps. • Follow solid engineering practices: version control, testing, CI/CD, and evaluation of AI output quality. • Integrate what you build with our enterprise systems, data, and APIs, with security considered from the start. • Stay with each project through deployment, adoption, support, and improvement. You own the outcome, not just the code. Make it enterprise-ready • Work with our security, architecture, governance, and compliance teams to get solutions ready for production. • Weigh trade-offs like cost, performance, reliability, and maintainability, and explain them in plain business terms. • Set up monitoring and feedback loops, track whether the solution is being used and delivering value, and adjust based on what you learn. • Help teams adopt what you build through training, feedback sessions, and change support. Share what you know • Explain AI capabilities, limits, and risks clearly to technical and non-technical audiences alike. • Document your designs and decisions so others can support and build on your work. • Coach teammates, review designs, and contribute to shared patterns and standards as the team grows. What We Are Looking For • Bachelor's degree in a technical field, or equivalent practical experience. • Five to eight years in software, solutions, data, or ML engineering, including at least two years building AI, ML, or automation solutions. • Solid programming skills in Python, JavaScript/TypeScript, C#, or a similar language, plus a willingness to use low-code platforms when they're the better fit. • Working knowledge of modern AI, including LLMs, RAG, agents, prompt engineering, and evaluation. • A current view of the frontier model landscape — including Claude, OpenAI, and Gemini models and the leading open-source models — and a practical sense of what each is good at. • Hands-on experience building, integrating, and deploying applications on Azure, working with APIs, cloud services, and authentication. We run our AI solutions on our own Azure infrastructure, so you will be working in it from day one. • Experience leading requirements conversations with business stakeholders and defining success measures with them. • A track record of owning projects end to end and getting them into production with limited direction. • Clear communication with both technical and business audiences, including senior leaders. Nice to Have • Experience applying AI or analytics in Quality (quality systems, complaint handling, CAPA, audits) or Commercial (sales, marketing, pricing, customer analytics) settings. • Experience shipping AI agents, RAG applications, or copilots to production. • Familiarity with orchestration frameworks such as LangGraph or Semantic Kernel, or with Model Context Protocol (MCP). • Experience with Power Platform or similar workflow automation tools. • Experience with containerization, monitoring, observability, and production support. • Background in business analysis, consulting, or product management. • Experience working in a regulated environment. Why Hologic At Hologic, our mission is simple: to enable healthier lives everywhere, every day. As a global leader in women's health, we develop innovative technologies that transform the detection, diagnosis, and treatment of breast cancer and other conditions affecting women. We offer: • The opportunity to own complex technical initiatives and drive them from concept to production. • The chance to work on secure, scalable, maintainable, enterprise-ready AI solutions. • Exposure to modern AI platforms, AI agents, RAG applications, copilots, intelligent workflows, automation solutions, and Responsible AI practices. • Collaboration across business, IT, security, architecture, governance, compliance, privacy, and operations teams. • The opportunity to contribute to reusable AI patterns, reference architectures, governance-aligned practices, and standards for enterprise-ready AI solutions. If you're motivated by exploring what's possible with AI, building strong partnerships, and delivering results that make a difference in women's healthcare, we would love to hear from you. Working Model: Hybrid - 3 Days in the office Salary: $95,500k to $149,400k The final offer will depend on experience, skills, and alignment with internal pay structures. In addition, we offer a comprehensive benefits package including 401k and insurances. Agency and Third Party Recruiter Notice: Agencies that submit a resume to Hologic must have a current executed Hologic Agency Agreement executed by a member of the Human Resource Department. In addition Agencies may only submit candidates to positions for which they have been invited to do so by a Hologic Recruiter. All resumes must be sent to the Hologic Recruiter under these terms or they will not be considered. Hologic’s employees are subject to third-party COVID-19 vaccination requirements, including from customers and governmental entities. Hologic is an equal opportunity employer and consistent with federal, state, and local requirements, will consider requests for reasonable accommodation based on disability or sincerely-held religious beliefs where it is able to do so without undue hardship to the company. Hologic, Inc. is proud to be an Equal Opportunity Employer inclusive of disability and veterans #LI-JD1

Requirements

Must-haves

Senior Applied AI Engineer
You should be comfortable starting from a vague problem rather than a written spec — asking good questions, defining what success looks like, and moving the work forward without waiting to be told what to do next.
Work with the business
Meet with business teams to find and prioritize problems where AI can genuinely help, and be honest about where it can't.
Run discovery sessions: ask good questions, map how the work gets done today, and pin down the actual problem before proposing anything.
Define what success looks like for each project, including the measures you will use to show it worked.
Turn rough ideas into clear problem statements, options, and plans that both leaders and engineers can act on.
Design and build
Design and build AI solutions such as copilots, agents, retrieval-augmented generation (RAG) applications, and workflow automations on the platforms we use today, including Azure OpenAI, Claude, and Microsoft Copilot.
Pick the right approach for each problem, whether that's custom code (Python, JavaScript/TypeScript, C#) or configuration on platforms like Power Automate or Logic Apps.
Follow solid engineering practices: version control, testing, CI/CD, and evaluation of AI output quality.
Integrate what you build with our enterprise systems, data, and APIs, with security considered from the start.
Stay with each project through deployment, adoption, support, and improvement. You own the outcome, not just the code.
Make it enterprise-ready
Work with our security, architecture, governance, and compliance teams to get solutions ready for production.
Weigh trade-offs like cost, performance, reliability, and maintainability, and explain them in plain business terms.
Set up monitoring and feedback loops, track whether the solution is being used and delivering value, and adjust based on what you learn.

Nice-to-haves

Experience applying AI or analytics in Quality (quality systems, complaint handling, CAPA, audits) or Commercial (sales, marketing, pricing, customer analytics) settings.
Experience shipping AI agents, RAG applications, or copilots to production.
Familiarity with orchestration frameworks such as LangGraph or Semantic Kernel, or with Model Context Protocol (MCP).
Experience with Power Platform or similar workflow automation tools.
Experience with containerization, monitoring, observability, and production support.
Background in business analysis, consulting, or product management.
Experience working in a regulated environment.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiazurepythonjavascripttypescriptci/cdml

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

401k