Director, Information Security
Director, Information Security
investcloud, inc.This job is no longer accepting applications
Job Description
- Technical Leadership: Lead a team of 4 senior security engineers — setting technical direction, reviewing code, owning architecture decisions, and ensuring every engineer grows in both traditional InfoSec depth and agentic AI engineering capability.
- Automated Security Platform: Own the design, deployment, and ongoing evolution of our intelligent security response platform — a Python-based, AI-driven pipeline that automates vulnerability discovery, contextual triage, reasoning, and graduated remediation across our full product estate.
- Autonomy Policy & Governance: Define and own the graduated automation policy — what the platform may execute automatically, what requires human approval, and what constitutes a break-glass escalation. You hold the senior technical authority for automated remediation decisions.
- Global InfoSec Interlock: Operate as the primary technical representative of the Bengaluru security engineering team in global InfoSec forums — owning the security posture reporting, KPI tracking (MTTA, SAST coverage, remediation velocity), and executive-level updates.
- InfoSec Transformation: Lead the progressive transition from reactive, manual vulnerability management to a proactive, automated, evidence-driven security practice — retiring manual triage queues, spreadsheet tracking, and ad hoc patching in favour of platform-driven workflows.
- Team Development: Hire, develop, and retain security engineers who are genuinely dual-track — capable of operating traditional security tooling and building and maintaining the agentic layer that reasons over it.
- 15+ years in information security engineering, with at least 8 years in a technical leadership or senior engineering management role — you must be credible as an engineer to the team you lead.
- Hands-on Python development experience — you write production-quality Python, not just review it. Security automation, API integration, and pipeline development are your native territory.
- Proven experience delivering a security engineering programme at scale — SAST/SCA/DAST across a multi-product estate, CI/CD security gate enforcement, vulnerability lifecycle management end-to-end.
- Direct experience with agentic AI or LLM-based automation in a production security context — confidence-scored decision pipelines, human-in-the-loop gate design, automated evidence generation.
- Experience designing and governing automated remediation policies — graduated autonomy models, kill-switch protocols, audit trail requirements, and SOC 2 or equivalent compliance mapping.
- Track record of building and developing dual-track security engineering teams — engineers who are both InfoSec practitioners and automation/AI builders.
- Background in FinTech, enterprise SaaS, or a regulated technology environment — practical understanding of how compliance obligations shape security architecture decisions.
Python (production-level)
- Snyk
- SonarQube
- Tenable
- Wiz
- LangChain / LangGraph
- Claude / GPT-4o APIs
- Jira / JSM
- CI/CD (GitLab CI)
- Datadog
- OWASP ASVS
- SOC 2
- CVSS
More Info
Job Type:
Industry:
Function:
Employment Type:
Key Skills
Compliance mapping
Agentic AI
Automated remediation policies
Vulnerability lifecycle management
LLM-based automation
About Company
Skills:
boundary scan , Python, Tcl, Jtag, Perl, IEEE 1687, MBIST, commercial ATPG and DFT insertion tools, BISR, IEEE 1149.1, silicon bring-up debug, ATPG, DFT verification, Modus, Tessent, scan and test compression, scripting and automation, IJTAG, IEEE 1838, DFT architecture and implementation, DFT tooling and standards
Skills:
data engineering , Hipaa, Microservices, Ehr, Application Development, Agile, Scrum, Integration, Emr, Devops, Hl7, Healthcare Interoperability Standards, Delivery Governance, FHIR, Executive Stakeholder Management, Cloud-native technologies, Financial Management, modernization, Commercial Negotiations, API Ecosystems, Mobile Data Platforms, HIS, Digital Personal Data Protection Act, PMS, Production Support, AI-assisted engineering
Skills:
Retrieval Augmented Generation (RAG), Java, Databases, Performance Engineering, Distributed Systems, Python, Cost optimization in cloud environments, Agent architectures and memory systems, Go, Vector search and indexing, Data and AI infrastructure concepts, LLM and inference systems, Production SaaS services at scale, Embedding pipelines, Reliability
Skills:
Machine Learning, scrapy, Sql, Nosql, Pandas, Gcp, Numpy, Spark, Azure, Python, AWS, scikit-learn, Ai, Analytics, R, BERT
Skills:
containerization , Microservices, Data architecture principles for AI-ready systems, Vector databases, Semantic search technologies, API design and integration patterns, Agentic design patterns, AI-assisted development practices, Responsible AI practices and governance, Engineering modernization, AI ML technologies and frameworks