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 solid 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 quick-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 modern 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 up-to-date 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 chance 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