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Specialist, AI Engineer

Job in 500001, Hyderabad, Telangana, India
Listing for: MSD
Full Time position
Listed on 2026-03-14
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Science Manager, Data Analyst
Job Description & How to Apply Below
This job is with MSD, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Job Description
The Opportunity     Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.
Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products.
Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats.
Our Technology Centres focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company's IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy.  

A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centres.

Role Overview   The AI Engineer (R2) will design, build, and deploy production-grade AI systems that power autonomous cyber defense and enterprise security optimization. This role focuses on developing agentic AI, decision engines, and multi-step reasoning systems that integrate directly into Microsoft Defender XDR, Sentinel, and related enterprise platforms.  This is not research or chatbot role. The AI Engineer will build AI systems that reduce manual effort, optimize operational workflows, score risk in real time, and enable safe autonomous enforcement across security platforms.
Design and deploy machine learning models for threat classification, anomaly detection, and risk scoring.
Build LLM-based agents capable of contextual reasoning, summarization, classification, and workflow execution.
Engineer prompt strategies and structured evaluation frameworks to ensure reliability and repeatability.
Develop multi-agent systems that automate operational tasks and drive measurable workforce efficiency gains.
Integrate AI outputs into enforcement platforms (e.g., conditional access triggers, device isolation logic, adaptive workflows).
Implement regression, classification, clustering, or anomaly detection models aligned to real-world telemetry.
Design guardrails, kill switches, and rollback mechanisms to ensure safe AI deployment in regulated environments.
Partner with Data Engineering to develop feature pipelines and production-ready datasets.
Build model monitoring and feedback loops to continuously improve precision and reduce false positives.
Contribute to ontology-driven reasoning and entity-aware AI decisioning where applicable.
What will you do in this role     3-6+ years of hands-on AI/ML engineering experience.
Strong proficiency in Python and modern ML frameworks (e.g., scikit-learn, PyTorch, Tensor Flow, or equivalent).
Experience deploying production AI systems integrated into enterprise platforms or APIs.
Demonstrated experience with LLM-based systems, prompt engineering, or agent-based workflows.
Strong understanding of supervised and unsupervised learning techniques.
Experience building evaluation metrics for model performance and business impact.
Ability to translate ambiguous operational problems into structured AI solutions.
Strong systems-thinking mindset and engineering discipline.

Required Skills:

Data Engineering, Design Applications, Information Security, Machine…
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