Engineering Manager, AI
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Engineering Manager, AI
Experience: 12+ years
Location: Bangalore / Coimbatore (Hybrid)
Location: Bangalore / Coimbatore (Hybrid)
About AppViewX
AppViewX is trusted by leading organizations around the world to reduce risk, ensure compliance, and increase visibility through machine identity management, AI security governance, and application infrastructure security.
We are building next-generation platforms that help enterprises discover, govern, secure, and manage AI agents, MCP servers, models, identities, and workflows across coding and non-coding environments.
As enterprises accelerate adoption of Agentic AI, LLMs, autonomous agents, and AI-powered workflows, AppViewX is enabling organizations to embrace AI innovation securely while maintaining governance, compliance, and operational resilience.
At AppViewX, you will work on the AVX ONE platform, which delivers certificate lifecycle management and PKI-as-a-Service through streamlined automation workflows designed to prevent outages, reduce security incidents, and support crypto-agility.
Role Overview
We are looking for an experienced Engineering Manager, AI to guide a high-impact team building enterprise-grade AI security, governance, and agent management platforms.
This role combines engineering leadership with strong technical depth in AI/ML systems, LLMs, distributed systems, cloud-native architectures, and security. You will help shape architecture, delivery, reliability, scalability, and security for AI-native products while mentoring high-performing engineering teams.
The ideal candidate is comfortable working across agent frameworks, distributed systems design, scalability, security controls, compliance requirements, and engineering execution.
Key Responsibilities
Engineering Leadership
- Build, mentor, and manage a team of 15–30 software engineers, architects, and technical leads.
- Advance engineering excellence through strong software development practices, architecture reviews, code quality, and operational rigor.
- Foster a culture of innovation, ownership, accountability, continuous learning, and customer focus.
- Establish career development plans, coaching frameworks, and performance processes for engineers.
AI Platform, Architecture, Governance and Security
- Lead the design, development, and delivery of enterprise-grade AI-native SaaS platforms focused on AI governance, compliance, policy enforcement, MCP security, AI risk management, and security analytics.
- Define and execute the technical roadmap for scalable, resilient, multi-tenant cloud-native systems aligned with business priorities and customer needs.
- Shape architectural direction across AI and platform services, including LLM integrations, AI gateways and proxies, security enforcement frameworks, event-driven architectures, and workflow orchestration systems.
- Establish and promote secure AI development practices, including controls for policy enforcement, prompt security, agent and MCP governance, audit logging, observability, and operational resilience.
- Ensure platform reliability, performance, scalability, and security using distributed systems principles, cloud-native technologies, and engineering best practices.
- Partner closely with Product Management, Security Research, Customer Success, and GRC teams to deliver solutions aligned with frameworks such as SOC 2, ISO 27001, NIST AI RMF, and OWASP LLM Top 10.
Reliability and Operations
- Promote operational excellence through observability, monitoring, incident management, and SRE best practices.
- Define SLAs, SLOs, and reliability goals for AI and platform services.
- Lead production readiness reviews and post-incident improvement efforts.
- Drive cloud cost optimization and platform efficiency initiatives.
Stakeholder Management
- Communicate technical vision, risks, trade-offs, and progress to executive stakeholders.
- Partner with customers and field teams to understand enterprise AI adoption challenges.
- Translate customer requirements into scalable product capabilities.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field.
- 12+ years of software engineering experience, including 4+ years leading engineering teams in a product development environment.
- Proven experience building and delivering enterprise-scale SaaS platforms using cloud-native architectures and distributed systems.
- Strong technical expertise in Generative AI, Large Language Models (LLMs), AI agents, and AI application architectures.
- Hands-on experience designing and integrating AI platforms, model services, APIs, and enterprise AI workflows.
- Deep understanding of software architecture, microservices, Kubernetes, containers, event-driven systems, and high-availability design principles.
- Experience implementing security, governance, compliance, and risk management controls within enterprise software products.
- Strong knowledge of public cloud platforms such as AWS, Azure, or GCP, including DevOps and observability practices.
- Demonstrated ability to guide engineering execution, mentor technical leaders, and establish strong engineering practices across teams.
- Excellent communication, judgment, stakeholder management, and problem-solving skills, with the ability to influence technical and business outcomes.
Our Values
At AppViewX, our values reflect how we work together in practice—not just what we aspire to. They guide how we collaborate, make decisions, and deliver outcomes.
- Clarity: We interact with transparency, simplicity, and shared purpose.
- Unity: We build unity through mutual respect, trust, and collaboration.
- Innovation: We stay curious, challenge assumptions, and drive continuous improvement.
- Speed: We act with urgency, focus, and follow-through to deliver results fast.
- Precision: We bring accuracy, consistency, and care to everything we do.
Why AppViewX?
AppViewX serves a broad global customer base, including Fortune 1000 companies across banking, media, and healthcare. Over the years, we have grown a diverse team, expanded our global presence across India, North America, the United Kingdom, and Australia, and continued to strengthen long-term customer trust through innovation and execution.
Equal Opportunity Statement
AppViewX is proud to be an Equal Employment Opportunity Employer. AppViewX provides equal employment opportunities to all employees and applicants regardless of race, color, national origin, ancestry, religion, citizenship status, gender, gender expression or identity, sexual orientation, age, marital status, military or veteran status, pregnancy, disability, genetic information, arrest record, or any other protected class under applicable law.
Skills
- Agentic AI
- AI
- Ai Enablement
- Analytics
- API
- Automation
- AWS
- Azure
- Cloud
- Cloud Native
- DevOps
- Distributed Systems
- Event Driven Architecture
- GCP
- Generative AI
- IAM
- ISO 27001
- Kubernetes
- LLM
- Machine Learning
- MCP
- Microservices
- Nist
- Observability
- OWASP
- PKI
- SaaS
- SOC 2
- SRE
- Stakeholder Management
- Unity
- Workflow Orchestration
As published by greenhouse · 7 questions
Basics
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter
Short answers (1)
- LinkedIn Profile optional
Pick from a list (6)
- Do you have at least 3+ years of hands‑on experience working as a Engineering Manager in a B2B SaaS / enterprise product company?
- Do you have at least 12 years of professional software engineering experience, including 4+ years leading engineering teams in a product development environment for enterprise/B2B SaaS?
- In your recent roles, what level of hands‑on responsibility have you had for designing and delivering AI/ML or LLM‑based platforms (e.g., AI agents, AI gateways, model services, or enterprise AI workflows)?
- Which of the following have you directly worked with in building or operating enterprise‑scale SaaS platforms? Select all that apply.
- What best describes your experience with building security, governance, and compliance controls into AI or cloud‑native platforms (e.g., policy enforcement, audit logging, SOC 2 / ISO 27001 alignment, NIST AI RMF, OWASP LLM Top 10)?
- What is the typical size and make‑up of engineering teams you have managed, and how long do you realistically see yourself committing to a high‑growth AI platform leadership role?