Boehringer Ingelheim Posted September 23, 2026

Senior AI Engineer for Cybersecurity Detection (Muntinlupa, Philippines, National Capital Region (NCR))

Muntinlupa, Philippines Type not listed
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Boehringer Ingelheim is the source of truth for this posting and owns the application process. We surface normalized context and market comparison you won't find on the original listing.

About this opportunity

The Position

Join Boehringer Ingelheim's Cyber Intelligence & Security Operations Center (CISOC) as a Senior Data Scientist / AI Engineer and play a key role in shaping the future of AI-driven cybersecurity operations. In this role, you will design, build, and optimize advanced multi-agent AI solutions that support security incident triage, decision-making, and workflow automation.

Working alongside cybersecurity experts, data scientists, and technology teams, you will develop intelligent systems that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), machine learning, and agent-based architectures to enhance operational efficiency and accelerate incident response. While experience in cybersecurity is beneficial, candidates with strong AI, machine learning, and agentic AI expertise from other domains are encouraged to apply.

Duties & Responsibilities

As a Senior Data Scientist or AI Engineer, you will be helping in designing and developing an advanced multi-agent system to support the triage of security incidents.

Design and maintain multi-agent architectures for triage and decision support.

Develop and refine machine learning models to assess and score incidents.

Integrate and orchestrate various tools and agents to automate and enrich the triage process.

Collaborate with project teams to ensure effective implementation and alignment with project goals.

Document system logic, workflows, and findings for stakeholders.

Requirements:

An ideal candidate will have

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field.

Equivalent professional experience may be considered in lieu of formal education.

Minimum of 5 years of experience in Data Science, AI Engineering, Machine Learning, or related technical roles.

Demonstrated success in developing and refining agent-based systems and machine learning models for decision support in enterprise environments.

Technical Capabilities

Proven experience designing, building, and deploying agent-based AI systems, including orchestration of multiple agents and integration with diverse tools, protocols (e.g., MCP), and data sources.

Hands-on expertise with: Large Language Models (LLMs)

Retrieval-Augmented Generation (RAG)

Machine Learning and AI-driven decision support systems

Agent orchestration frameworks and multi-agent architectures.

Deep understanding of agent toolchains, agent orchestration frameworks, and best practices for integrating and scaling agent-based architectures in enterprise environments.

Strong proficiency in Python and relevant programming languages for developing, integrating, and automating AI solutions.

Practical experience with containerization and deployment technologies such as Docker and OpenShift; familiarity with MLflow or similar platforms for model lifecycle management is highly valued.

Demonstrated ability to operationalize and maintain AI agents, including monitoring, troubleshooting, and continuous improvement in production environments.

Experience integrating agent-based systems with enterprise protocols and APIs, ensuring robust, secure, and scalable solutions.

Certifications in Data Science, AI, or Machine Learning (e.g., Azure AI Engineer, AWS Machine Learning, or similar) or any additional credentials in automation, agent-based systems, or related areas are valued.

Additional competencies

Ability to work effectively with cross-functional teams, including project stakeholders and technical experts.

Strong written and verbal communication skills to document system designs and present findings to both technical and non-technical audiences.

Excellent troubleshooting and analytical skills for developing creative solutions to complex challenges.

Willingness to stay current with industry trends, technologies, and best practices in AI and automation.

High level of precision in designing, tuning, and evaluating models and agent workflows to ensure reliable outcomes.

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Job details

Seniority
Senior
Function
Information Technology
Therapeutic area
Not listed
Location
Muntinlupa, Philippines
Employment type
Not listed

How this role compares

Computed from every other active Information Technology role in our database, not just this employer's listings.

We currently track 393 comparable Senior Information Technology roles across 49 biopharma companies.

393Comparable roles tracked
367Currently active
49Companies hiring similar roles
28Countries represented

Salary context

61 of 393 peers report a salary range (USD, annualized)

Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.

This roleSubject Not listed on this posting
Highest disclosed · Sr. AI Science Lead · Lilly $267,000/yr – $391,600/yr
Peer group range $98,050 – $329,300 (median $183,750)

Where these roles are based

Top locations among the 393 comparable roles

India183
United States113
Spain22
Poland10
Portugal8
Japan5

+ 22 more countries

Seniority mix

393 of 393 peers have a known seniority level

Senior271
Principal67
Associate Director55

Therapeutic area mix

1 of 393 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden

Vaccines & Infectious Disease1

Similar opportunities

The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.

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Notify me about similar jobs

Get an email when we spot other openings like this one – same job function, comparable seniority, roles you'd actually want to see.

How we calculate "similar"

No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.

Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.

60%
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Unmatched or unknown dimensions score exactly the same: 0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.