Vice President of Engineering

INNEFU LABS

VP — Engineering

AI-Native Data Analytics & Information Security Solutions

Location

Delhi, NSP — 5 Days WFO

Experience

15+ Years (6+ in leadership)

Employment

Full-Time

Company Overview

Founded in 2010, Innefu Labs is a cutting-edge AI-driven R&D organization focused on delivering advanced Data Analytics and Information Security solutions. With innovation at its core, the company was established with a mission to drive high-end R&D that results in globally competitive products and contributes to national economic growth.

With over 100+ successful deployments across the Indian Subcontinent, Middle East, and Southeast Asia, Innefu has emerged as a de facto leader in AI for National and Cyber Security. Our proprietary product suite serves a diverse clientele, including Defense & Intelligence agencies, Law Enforcement, Financial Intelligence Units, BFSI, and several Fortune 500 companies.

Trusted by some of the most sensitive and mission-critical organizations, we bring unparalleled expertise in handling secure and large-scale installations. Our core philosophy revolves around building state-of-the-art, problem-solving products backed by exceptional customer support to ensure 100% client satisfaction.

Role Overview

We are seeking a strategic and hands-on VP of Engineering to own the technology vision, engineering organization, and delivery outcomes across Innefu's AI/ML-powered Data Analytics and Information Security product suite. This is a senior leadership role reporting into the executive team, responsible for scaling engineering capability, driving architectural excellence, and ensuring the organization can deliver secure, high-performance products at the pace and reliability our national security and enterprise clients demand.

Key Responsibilities

Organizational & Executive Leadership

• Define and own the engineering vision, strategy, and multi-quarter roadmap in partnership with the executive leadership team.
• Build, scale, and lead a multi-team engineering organization, including Engineering Managers, Tech Leads, and Data Engineering functions.
• Own engineering headcount planning, budgeting, and vendor/tooling decisions.
• Drive org-wide performance management, career frameworks, and leadership development for managers reporting into this role.
• Represent engineering in leadership/board-level discussions on product strategy, delivery risk, and technology investment.

Delivery & Agile Governance

• Set and govern engineering-wide delivery standards: sprint cadence, velocity tracking, release predictability, and quality gates.
• Ensure cross-team alignment with the product roadmap; resolve cross-functional dependencies and prioritization conflicts.
• Establish metrics and reporting for engineering health (delivery predictability, defect rates, system uptime) for leadership visibility.

Technical & Architectural Ownership

• Own the enterprise-wide technical architecture strategy — scalability, security, and performance — across Python-based microservices and JavaScript-based service/UI layers.
• Set standards for graph-based data modeling (Neo4j) and search/analytics infrastructure (Elasticsearch) used across the product portfolio.
• Define and enforce engineering best practices: coding standards, code review culture, testing, and CI/CD maturity across teams.
• Remain hands-on when needed — reviewing critical architecture decisions, unblocking complex technical problems, and setting technical direction rather than day-to-day coding.

Infrastructure, Security & Deployment

• Own the strategy for Docker-based on-premises development and deployment, particularly for secure, air-gapped, or classified environments typical of defense/intelligence clients.
• Partner with DevOps and Security leadership to harden CI/CD, version control practices, and deployment governance across on-prem and hybrid environments.
• Ensure architecture and infrastructure decisions meet the compliance and data-sensitivity requirements of government, defense, and BFSI clients.

Cross-functional & Stakeholder Management

• Act as the primary engineering counterpart to Product, Business Stakeholders, Sales/Pre-Sales, and QA leadership.
• Lead executive-level discussions on technical risk, major incidents, and product/technology trade-offs.
• Champion a strong engineering culture of ownership, mentorship, and continuous improvement across the organization.

Required Skills & Qualifications

• 15+ years of software development and engineering experience, including 6+ years in senior leadership roles managing managers or multiple teams.
• Deep hands-on background in Python, with strong working knowledge of frameworks such as Django, Flask, and FastAPI.
• Working knowledge of JavaScript for full-stack and service-layer oversight.
• Strong experience with Elasticsearch for search and analytics at scale.
• Experience with graph databases (Neo4j) for relationship-driven data modeling and analytics use cases.
• Proven experience owning Docker-based, on-premises development and deployment for enterprise or secure/air-gapped environments.
• Familiarity with PostgreSQL and NoSQL databases at an architectural decision-making level.
• Strong understanding of data engineering pipelines and ETL processes (good to have, especially if leading Data Engineering functions).
• Demonstrated experience owning Agile delivery governance across multiple teams — not just facilitating ceremonies, but setting org-wide delivery standards.
• Strong experience with Git-based version control and CI/CD strategy at an organizational level.
• Deep expertise in scalable architecture, high availability, and system performance at an enterprise portfolio level.
• Prior experience in budget ownership, vendor management, and executive/board-level communication.
• Exceptional leadership, stakeholder management, and strategic problem-solving abilities.