ANSR
Website:
ansrinc.com
Company:
https://www.linkedin.com/company/ansr-global
Seniority: Mid-Senior level
Industries: Medical Equipment Manufacturing
Job details:
ANSR is hiring for one of its clients.
About ANSR MedTech:
Who We Are:
ANSR MedTech Capability Center is a new global innovation hub being established in India for a Fortune 100 Fastest-Growing Company in the MedTech sector. Built in partnership with ANSR, the center draws on ANSR’s proven experience in establishing and scaling high-performance Global Capability Centers (GCCs) for leading global enterprises.
ANSR MedTech center brings together world-class engineering, product, and technology talent to build next-generation healthcare platforms and solutions that power global operations.
Our Vision:
To build a next-generation MedTech capability center that powers global healthcare innovation. We envision:
- High-impact innovation hubs shaping global product and technology roadmaps
- Centers that go beyond support functions to drive core engineering and platform development
- Sustainable, scalable ecosystems that nurture world-class MedTech talent
- Capability centers that directly influence patient outcomes worldwide
At its core, the ANSR MedTech Capability Center is about enabling innovation that touches lives at scale.
Job Summary:
The Principal Forward Deployed Engineer will work directly with business, functional, and clinical stakeholders to design, build, and deploy AI and data products that solve high-value problems in the field. Combining hands-on software, data, and AI engineering with strong customer engagement, this role takes solutions from initial workshop and prototype through production deployment and adoption, closing the gap between what the business needs and what the platform delivers.
This role reports to the Director of Applied AI and operates within a multi-disciplinary delivery organization, partnering closely with applied AI engineers, data scientists, data engineers, analytics engineers, and product owners while acting as the on-the-ground technical partner to the stakeholders it serves.
About IACTO:
- At ANSR MedTech, the Insights & Analytics (I&A) Center of Excellence is built as a single, integrated analytics organization with two closely partnered focus areas: Growth aligned analytics and CTO aligned analytics.
- Both work together to ensure analytics drives real outcomes at enterprise scale.
- Growth Aligned Insights & Analytics
- Growth aligned I&A teams focus on turning data into decisions.
- They work closely with business leaders to understand context, analyze data, and deliver insights that directly inform commercial, product, and operational actions.
- These roles are best suited for people who enjoy:
- Working close to the business and stakeholders
- Translating complex data into clear insights and recommendations
- Driving measurable impact through analytics
CTO Aligned Insights & Analytics:
- CTO aligned I&A teams focus on building and operating the data and AI foundation that enables analytics at scale.
- They design, build, and maintain platforms, pipelines, models, and governance that ensure analytics is secure, reliable, and repeatable.
- These roles are best suited for people who enjoy:
- Building scalable data platforms and AI capabilities
- Engineering high quality, production ready data solutions
- Establishing standards, reliability, and long term sustainability
How the Teams Work Together:
- Growth defines what insights matter and how they are used
- CTO enables how those insights are delivered at scale
- Teams operate as one connected analytics organization, with clear ownership and shared outcomes
- This model allows ANSR MedTech to deliver fast, meaningful insights while building a strong, enterprise grade analytics foundation for long term growth.
Key Responsibilities:
- Embed directly with business, functional, and clinical stakeholders to understand their workflows, pain points, and goals, and to identify high-impact opportunities for AI and data solutions
- Run discovery workshops and working sessions with stakeholder teams, producing target-state mockups and scoping solutions in real time to lock requirements quickly
- Rapidly prototype and demonstrate solutions, from proof-of-concept to working pilot, to validate value before committing to a full build
- Design, build, and ship end-to-end AI and data products in the field, spanning data engineering, LLM/GenAI and ML integration, back-end services, and lightweight front-ends
- Integrate solutions with enterprise data sources, platforms, and APIs, handling the realities of real-world data and systems
- Own deployment and product ionization of solutions, including environment setup, CI/CD, configuration, and hardening, so pilots become reliable, supportable products
- Drive adoption in the field by onboarding and training users, gathering feedback, and iterating quickly to improve fit and usage
- Act as the primary technical point of contact and trusted advisor to the senior (VP-level) business, functional, and clinical stakeholders you serve — framing problems, setting direction, and translating fluently between business needs and engineering delivery
- Set the local technical direction for field AI solutions — making architecture, modeling, and design decisions in-market, establishing standards and reusable patterns, and mentoring Forward Deployed (Staff) Engineers.
- Instrument solutions for monitoring and support, and establish clear handover paths to platform and product teams for long-term ownership
- Feed field learnings, reusable components, and product gaps back to the core Applied AI and platform teams to strengthen shared capabilities
- Uphold security, privacy, Responsible-AI, and compliance standards for every deployment in a regulated MedTech environment
- Balance speed and quality, making pragmatic engineering trade-offs that deliver value fast while keeping solutions maintainable
- Collaborate with applied AI engineers, data scientists, data engineers, and analytics engineers to leverage and extend the COE's platforms, patterns, and reusable components
Qualifications:
- Bachelor's or Master's degree in computer science, data science, engineering, or a related quantitative field, or equivalent hands-on experience
- 12+ years of hands-on experience building software, data, or AI solutions, ideally in customer-facing, consulting, or embedded delivery settings
- Strong full-stack engineering ability: proficiency in Python and SQL, with experience across data pipelines, APIs and back-end services, and at least lightweight front-end delivery
- Hands-on experience integrating AI/ML or generative-AI/LLM capabilities into working applications (e.g., OpenAI, Claude, Gemini; RAG; prompt engineering)
- Experience with cloud data and AI platforms (Azure — Databricks, Data Factory, Azure ML/Foundry, App Services — or equivalent) and CI/CD
- Proven ability to work directly with business stakeholders: running workshops, gathering requirements, and translating ambiguous problems into deployed solutions
- Comfort operating with autonomy and ambiguity in the field, owning solutions end-to-end from prototype to production
- Excellent communication and interpersonal skills, with the ability to build trust with non-technical stakeholders and communicate technical trade-offs clearly
- Willingness to travel to or embed with stakeholder teams as needed
Preferred skills:
- Experience in MedTech, life sciences, healthcare, pharma, or other regulated industries
- Experience with agentic frameworks and orchestration, vector and retrieval stores (e.g., FAISS), and content-safety or guardrail tooling
- Experience with Databricks (SQL, Unity Catalog) and the broader Azure AI ecosystem
- Familiarity with data visualization/BI (Power BI) and rapid app development (Power Platform) for fast, stakeholder-facing delivery
- Prior experience as a forward deployed engineer, solutions engineer, delivery/field engineer, or technical consultant, and familiarity with Responsible-AI / GRC frameworks
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