AI Technical Manager
About Biz4Group
Biz4Group is an AI-first technology consulting and product engineering company building enterprise-grade software and AI solutions for startups, SMBs and Fortune 500 companies.
Our work spans 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 through the next phase of software development, where AI is becoming part of how products are designed, built, tested and delivered.
This role is for someone who combines strong engineering fundamentals, AI expertise, product thinking and business understanding .
Role Overview
As an AI Technical Manager , you will be responsible for the technical direction and engineering execution of AI-powered products and enterprise applications.
You will lead teams, make architecture decisions, drive responsible AI adoption, improve engineering productivity and ensure that technology decisions are aligned with customer needs and business outcomes .
This is not a traditional people-management role.
We are looking for someone who can think like a product owner, operate like an architect, lead like an engineering manager and execute with the speed required in a fast-moving AI company.
Key Responsibilities
1. AI-First Engineering Leadership
Lead engineering teams building AI-powered products and enterprise solutions.
Drive practical adoption of AI across the software development lifecycle.
Establish standards for AI-assisted development, testing, code review and delivery.
Identify where AI can improve engineering productivity, quality and speed.
Mentor engineers on modern AI-native development practices.
Build a culture of ownership, technical excellence and continuous learning.
2. Technical Architecture & Engineering
Define scalable and maintainable application architectures.
Lead architecture decisions across backend, AI, APIs, databases and cloud infrastructure.
Design enterprise-grade systems using Python and JavaScript/TypeScript .
Lead API-first, event-driven and integration-heavy architectures.
Review system design, technical decisions and critical code.
Ensure security, scalability, maintainability and performance are considered from the beginning.
3. AI Engineering
Lead the development and integration of production-grade AI systems, including:
LLM-powered applications
AI agents
Agentic workflows
Multi-agent systems
Retrieval-Augmented Generation (RAG)
Enterprise AI assistants
AI automation
AI orchestration
Model and tool integrations
AI evaluation and monitoring
Work with models and platforms across OpenAI, Anthropic, Google and open-source ecosystems where appropriate.
The focus should always be on solving the business problem first and selecting the right AI approach second.
4. MCP & Intelligent Integrations
Take ownership of modern AI-to-system integration using Model Context Protocol (MCP) .
Responsibilities include:
Design and develop MCP servers.
Connect AI agents with enterprise applications and internal tools.
Enable AI systems to work with CRMs, ERPs, databases and business applications.
Design tool-use and orchestration architectures.
Implement authentication, authorization and permission controls.
Establish standards for secure and maintainable MCP implementations.
Identify opportunities where MCP can simplify enterprise AI integrations.
5. AI-Assisted Development & Vibe Coding
AI-assisted development is becoming a core engineering capability at Biz4Group.
You will:




Promote high-quality AI-assisted development and Vibe Coding .
Help teams use AI coding tools effectively without compromising engineering standards.
Define practices for prompting, code generation, review and validation.
Ensure AI-generated code meets production standards.
Introduce automated testing and validation wherever possible.
Measure whether AI adoption is actually improving development speed and quality.
The goal is not simply to write more code faster .
The goal is to build better software faster without sacrificing quality.
6. Product & Business Thinking
Technology decisions should always connect back to the customer's business problem.
You will:
Understand the problem before recommending technology.
Convert business requirements into scalable technical solutions.
Work closely with Product, Sales, Delivery and customers.
Identify technical approaches that improve customer value.
Balance speed, quality, cost and long-term maintainability.
Identify opportunities to turn repeated project requirements into reusable products, components or platforms.
Help teams move from a project-delivery mindset to a product-delivery mindset .
7. Engineering Team Leadership
Lead, mentor and develop engineering teams.
Build technical capability across AI, architecture and contemporary development.
Participate in technical hiring and interviews.
Identify skill gaps and create development plans.
Establish clear technical ownership within teams.
Support engineers in solving complex technical problems.
Build a culture where engineers take ownership instead of waiting for instructions.
8. Delivery & Quality
Ensure projects are technically ready for development before execution begins.
Identify technical risks and dependencies early.
Improve engineering estimation and delivery predictability.
Establish strong testing and QA practices.
Reduce production defects and technical rework.
Ensure proper documentation and knowledge transfer.
Maintain high standards for customer experience and production reliability.
Core Technical Expertise
Programming
Must Have:
Python — strong/expert level
JavaScript / TypeScript — strong/expert level
AI & LLM
Strong hands-on understanding of:
LLM integration
AI agents
Agentic AI
Multi-agent systems
Prompt engineering
RAG
Embeddings
Vector databases
AI evaluation
Agent orchestration
AI observability and monitoring
MCP
Strong practical understanding of:
Model Context Protocol
MCP server development
Tool integration
Tool orchestration
Context management
AI-to-enterprise system integrations
Authentication and authorization for AI tools
Backend
Experience with several of:
FastAPI
Django
Flask
Node.js
Express.js
REST APIs
GraphQL
WebSockets
Cloud & DevOps
Experience with:
AWS, Azure or Google Cloud
Docker
Kubernetes
CI/CD
Infrastructure as Code
GitHub Actions
Monitoring and observability
Databases
Experience with:
PostgreSQL
MongoDB
Redis
Vector databases such as Pinecone, Weaviate, Qdrant, Chroma or similar
Business & Product Expectations
The right person should be able to answer:




What business problem are we solving?
Why is AI required for this problem?
What is the simplest architecture that can solve it?
How will we measure whether the solution works?
Can this become reusable across multiple customers?
What will it cost to operate at scale?
You should be comfortable challenging technical decisions when they do not make business sense and explaining complex technology in simple business terms.
Required Experience
9+ years of software engineering experience.
5+ years of technical/team leadership experience.
Strong hands-on experience building production software.
Experience building and deploying AI-powered applications.
Strong Python and JavaScript/TypeScript expertise.
Practical experience with LLM-based applications and AI agents.
Strong understanding of system architecture and enterprise integrations.
Experience with MCP servers or similar AI tool-integration architectures.
Experience working with cloud platforms and modern DevOps practices.
Experience working with product, delivery and customer-facing teams.
Experience in SaaS, PropTech, HealthTech, FinTech, enterprise software or other domain-driven products is an advantage.
What We Look For
More than the technology stack, we are looking for someone with:
Product mindset over project mindset
Strong ownership and accountability
Business-first thinking
Strong architectural judgment
Ability to simplify complex problems
High engineering standards
Practical AI expertise
Curiosity and continuous learning
Strong communication
Ability to challenge assumptions
Ability to mentor and develop engineers
Bias toward execution
Strong customer orientation
Success in This Role
In the first 12 months, success will be measured by tangible improvements in:
Engineering
Engineering productivity
Development speed
Code quality
Production stability
Reduction in defects and rework
AI Adoption
Meaningful adoption of AI-assisted development
Production deployment of AI-powered solutions
AI engineering standards across teams
Effective use of AI agents and MCP-based integrations
Delivery
Delivery predictability
Technical risk reduction
Faster problem resolution
Improved engineering quality
People
Growth of engineering capability
Stronger technical ownership
Better mentoring and knowledge sharing
Stronger technical leadership pipeline
Business
Better customer outcomes
Reusable technology and product components
Improved delivery efficiency
Contribution to new AI-led business opportunities
Why Join Biz4Group?
Build in the AI Era
Work on AI agents, enterprise automation, LLM applications, MCP and AI-native software products.
Influence Technical Direction
You will have an opportunity to influence architecture, engineering practices and AI adoption across the organization.
Build Products, Not Just Projects
Work with teams that are increasingly focused on turning customer problems into scalable products and reusable solutions.
Work Across Domains
Get exposure to enterprise use cases across AI, SaaS, PropTech, HealthTech, FinTech and other technology domains.
Grow as a Technical Leader
The role provides an opportunity to grow beyond engineering management into AI architecture, product strategy and technology leadership .
The Person We Are Looking For
If you are someone who can understand a business problem, design the right technical solution, build it with modern AI practices, guide engineers through execution and take ownership of the final outcome , this role is for you.

📌 AI Technical Manager (Jaipur)
🏢 Biz4Group
📍 Jaipur