AI Technical Manager
- Compensation
- Not disclosed
- Location
- Jaipur, RJ, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Not specified
- Posted
Skills
Nice to have
- 8–15 years of software engineering experience.
- 3+ years leading engineering teams.
- Hands-on experience building AI-powered enterprise products.
- Experience deploying production-grade LLM applications.
- Experience with MCP servers and AI tool integrations.
- Experience in SaaS, PropTech, HealthTech, FinTech, or enterprise software.
- Strong system design and software architecture expertise.
- Proven track record of delivering scalable products.
Full description
About Biz4Group
Biz4Group is an AI-first technology consulting and product engineering company building enterprise-grade software solutions for startups, SMBs, and Fortune 500 companies. We specialize in AI agents, enterprise automation, SaaS platforms, PropTech, HealthTech, FinTech, and custom software development.
We are looking for an AI Technical Manager who can lead engineering teams in the era of AI-assisted software development. This role is for someone who combines deep technical expertise with business thinking, product ownership, and modern AI engineering practices.
Role Overview
As an AI Technical Manager, you will lead engineering teams in designing, developing, and delivering AI-native products and enterprise software. You will drive AI adoption across the engineering lifecycle, improve developer productivity through AI, mentor teams on modern engineering practices, and ensure every solution creates measurable business value.
This is not a traditional engineering manager role. We are looking for someone who can think like a product leader, architect like a senior engineer, and execute like a startup founder.
Key Responsibilities
AI-First Engineering Leadership
- Lead multiple engineering teams developing AI-powered applications.
- Drive organization-wide adoption of AI across software development and delivery.
- Define engineering standards for AI-assisted development and quality assurance.
- Mentor developers in AI-native engineering workflows and best practices.
- Build a high-performance engineering culture focused on innovation and ownership.
Technical Leadership
- Architect scalable cloud-native applications.
- Design enterprise-grade backend systems using Python and JavaScript/TypeScript.
- Lead API-first and event-driven architectures.
- Design secure, scalable, and maintainable software systems.
- Review architecture, code quality, and technical decisions.
AI Engineering
- Build and integrate LLM-powered applications.
- Design Agentic AI systems and autonomous workflows.
- Implement Retrieval-Augmented Generation (RAG) solutions.
- Develop multi-agent systems for enterprise automation.
- Integrate AI models from OpenAI, Anthropic, Google, and open-source ecosystems.
- Design AI evaluation, monitoring, and optimization frameworks.
MCP & AI Integration
- Design and implement Model Context Protocol (MCP) servers.
- Build secure integrations between AI agents and enterprise systems.
- Enable AI applications to interact with internal tools, CRMs, ERPs, databases, and business workflows through MCP.