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About the Role

As a Senior AI Security Engineer, you will operate at the frontier of Artificial Intelligence and Cybersecurity. Your mission is to architect, secure, and future-proof our pioneering AI-first platform and autonomous agentic workflows that drive the next generation of drug discovery pipelines. You will design custom risk management frameworks tailored to the unique threat landscape of AI in life sciences, establish strict governance over critical model artifacts, and embed seamless security controls directly into distributed training and inference infrastructure. You will serve as the technical anchor bridging machine learning engineering, platform architecture, and adversarial defense. Your work will ensure that breakthrough scientific research is paired with an uncompromising, resilient defense safeguarding invaluable intellectual property while accelerating our innovation velocity.

Responsibilities

Conduct cutting-edge threat modeling focused on AI/ML vulnerabilities, engineering a comprehensive risk management framework tailored to an AI-powered life sciences platform.
Partner with AI teams to establish a granular inventory, classification and protection framework for ML models’ weights, code, and training data.
Design and deploy scalable guardrails, robust sandboxing, and real-time monitoring controls for our extensive LLM ecosystem, including ADK, MCP, and autonomous agentic workflows.
Partner with ML researchers and platform engineers to design and implement robust security controls across the entire ML lifecycle—from data ingestion and training pipeline integrity to inference runtime controls.
Act as the primary technical expert for AI security incidents, deploying advanced machine learning techniques to automate threat hunting, anomaly detection, and signatureless mitigation specific to LLMs.
Bridge the gap between complex AI architectures and emerging global regulations (e.g., EU AI Act) by automating risk posture monitoring and continuous compliance metrics.
Pioneer the practical implementation of Isomorphic Labs' AI Safety standards, working in close coordination with Legal, Compliance, and external partners like Google DeepMind.

Requirements

Deep conceptual and practical understanding of deep learning frameworks (e.g., JAX, PyTorch, TensorFlow), large-scale cloud training or inference infrastructure, and LLM ecosystems.
Strong familiarity with AI security threat vectors (prompt injection, model inversion, data poisoning) and frameworks like OWASP Top 10 for LLMs or MITRE ATLAS.
Proven experience securing agentic frameworks (ADK, MCP), agentic first infrastructure and implementing robust agent-to-agent (A2A) identity and access controls.
Solid proficiency in cloud platform security (GCP preferred), including container security, multi-cloud/SaaS integrations, and strict network isolation boundaries.
Proven ability to define and execute pragmatic mitigation strategies that balance a rigorous security posture with the high-velocity needs of a world-class scientific research organization.
Ability to write production-grade code (Python preferred) to build custom security tooling, automate telemetry collection, or enforce policy layers.
Exceptional skills in navigating ambiguity, building trusted relationships with AI researchers, and clearly translating complex machine learning risks into actionable engineering tasks for leadership.
Experience conducting empirical vulnerability research or executing simulated attacks against LLMs, agent networks, and core ML backends.
Prior exposure to BioTech, Pharma, and/or Deep Tech industries where data integrity, intellectual property protection, and regulatory compliance (GxP) are paramount.
BSc, MSc, or PhD in Computer Science, Machine Learning, Cybersecurity, or a related quantitative field.
Relevant security or cloud credentials (e.g., OSCP, Professional Cloud Security Engineer) or specialized training in ML security.

Skills

AI/ML Engineering
Deep learning frameworks (JAX, PyTorch, TensorFlow)
Large-scale cloud training or inference infrastructure
LLM ecosystems
AI security threat vectors (prompt injection, model inversion, data poisoning)
OWASP Top 10 for LLMs
MITRE ATLAS
Agentic frameworks security
Agentic first infrastructure
Agent-to-agent (A2A) identity and access controls
Cloud platform security (GCP)
Container security
Multi-cloud/SaaS integrations
Network isolation
Risk assessment
Mitigation strategies
Software Development
Automation
Python
Security tooling
Telemetry collection
Policy enforcement
Translational Communication
AI Red Teaming
Regulated Environments
BioTech
Pharma
Deep Tech
Data integrity
Intellectual property protection
Regulatory compliance (GxP)
Computer Science
Machine Learning
Cybersecurity
Advanced Certifications
OSCP
Professional Cloud Security Engineer
ML security

Location

Remote
Hybrid

Work Type

Hybrid

Experience Level

Senior

Education Level

BSc, MSc, or PhD in Computer Science, Machine Learning, Cybersecurity, or a related quantitative field.

About the Company

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease.
Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed.
Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases.
We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.
Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.

Equal Opportunity

We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.