About this role
AlphaSense's GRC team is building a modern compliance and risk infrastructure that replaces traditional manual processes with automated, AI-native systems. This function acts at the intersection of security engineering and compliance operations, designing technical automation for control validation, evidence gathering, and platform integration.
In this role, the engineer will lead the charge in creating continuous compliance pipelines and owning the governance architecture for AI and agentic systems. Responsibilities include building policy-as-code programs, connecting security toolchains to GRC platforms, and deploying LLM-driven workflows for tasks like narrative drafting and risk analysis.
The ideal candidate brings an AI-native mindset, utilizing language models for substantive work while exercising rigorous judgment regarding human oversight and risk. This position suits a technical professional with a background in security, risk management, or GRC who wants to shape industry standards rather than follow conventional playbooks.
What you will do
- Design and build automated compliance testing pipelines to continuously validate control adherence across cloud infrastructure, SaaS platforms, and internal systems.
- Manage the technical configuration and integration of GRC platforms through custom API integrations and automated evidence connectors.
- Develop AI-assisted workflows for evidence summarization, control narrative drafting, risk analysis, vendor questionnaire triage, and policy gap detection.
- Establish the governance framework, policies, and control sets that dictate how AI and agentic systems are built and deployed.
- Implement a policy-as-code program using version control, peer reviews, and enforceable automated checks instead of static documents.
- Instrument controls with observability tooling to provide the GRC team with real-time signals on control health.
- Integrate GRC tooling with the broader security stack including SIEM, EDR, CSPM, identity platforms, and vulnerability management.
What you need
- Six or more years of professional experience in GRC, information security, risk management, or IT audit within a SaaS or cloud-native environment.
- Demonstrated understanding of security and compliance frameworks such as SOC 2, ISO 27001, NIST CSF 2.0, and CIS Controls, along with working knowledge of ISO 42001 and NIST AI RMF.
- An AI-native mindset utilizing tools like LLMs, agents, and automation for substantive tasks like analysis, drafting, and evidence gathering.
- Proficiency with GRC platforms used for evidence management and control testing, including Drata, Vanta, AuditBoard, or ServiceNow GRC.
- Familiarity with cloud environments like AWS, Azure, or GCP alongside associated security posture tooling such as CSPM, SIEM, and identity platforms.
- Direct experience supporting external audits across security or privacy domains through evidence collection, control walkthroughs, and auditor interaction.
- Hands-on background implementing automated control collection and continuous control monitoring via pipelines and integrations.
Skills and tech stack
Questions candidates ask
Where is AlphaSense located?
AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. The location for this specific posting is India.
What kind of AI experience is required for this role?
Candidates must have an AI-native mindset, using AI tools like LLMs, agents, and automation for real, substantive work including analysis, drafting, evidence gathering, and workflow automation. They must also apply judgment about where AI creates leverage and where a human must stay in the loop.
What frameworks will this engineer work with?
The role requires a strong understanding of security and compliance frameworks including SOC 2, ISO 27001, NIST CSF 2.0, and CIS Controls, alongside working knowledge of ISO 42001 and NIST AI RMF.
What is the primary goal of the GRC engineering function at AlphaSense?
The goal is continuous compliance infrastructure that generates its own proof, creating a function that is automated, AI-native, and architected like a product rather than operated like a process.