Role Overview

We are looking for a hands-on Technical Lead AI Engineering to lead AI engineers and develop, deploy, and maintain production-grade AI solutions. The role requires robust technical expertise, coding proficiency, architecture design, code reviews, team mentoring, and end-to-end ownership of AI application delivery.

The ideal candidate should have practical experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and AI orchestration frameworks, along with strong software engineering and deployment skills.

Key Responsibilities

- Lead AI engineering projects from requirement analysis and solution design through development, testing, and production deployment.
- Design and develop scalable AI applications, APIs, microservices, and reusable software components.
- Build AI solutions using GenAI, LLMs, RAG, Agentic AI, Model Context Protocol (MCP), Computer Vision, Voice AI, and Document Intelligence.
- Define technical architecture, engineering standards, and development best practices.
- Plan and track engineering activities, manage technical dependencies, and resolve development blockers.
- Conduct code reviews and ensure code quality, performance, security, and maintainability.
- Mentor AI engineers and support technical decision-making and knowledge sharing.
- Collaborate with cross-functional teams and stakeholders to ensure timely delivery of projects.
- Support sprint planning, testing, release management, deployment, and production troubleshooting.
- Ensure AI applications are scalable, reliable, secure, observable, and cost-efficient.
- Drive the adoption of reusable frameworks, tools, and modern AI engineering practices.





Required Skills and Qualifications

- 6+ years of experience in Software Engineering, AI/ML Engineering, GenAI, or AI Platform Development.
- Proven experience building and deploying production-grade AI applications.
- Strong hands-on experience with Python, REST APIs, microservices, SQL, and distributed systems.
- Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, MCP, and AI orchestration.
- Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent AI development frameworks.
- Experience designing and developing scalable backend services and AI-powered applications.
- Familiarity with Docker, Kubernetes, CI/CD pipelines, and cloud-based deployment.
- Understanding of MLflow, model lifecycle management, and application observability tools.
- Experience leading engineering teams, conducting code reviews, and mentoring developers.
- Strong problem-solving, communication, technical decision-making, and stakeholder-management skills.

Preferred Qualifications

- Experience leading the end-to-end delivery of enterprise-grade AI solutions.
- Knowledge of prompt engineering, LLM evaluation, AI guardrails, and responsible AI practices.
- Experience with MLOps/LLMOps, model monitoring, version control, and automated deployment.
- Understanding of AI security, data privacy, governance, and regulatory compliance.
- Experience optimizing AI applications for accuracy, latency, scalability, and operational cost.
- Ability to evaluate emerging AI technologies and translate them into practical business solutions.
- Experience establishing reusable frameworks, engineering standards, and best practices.

📌 AI Technical Lead (Bengaluru)
🏢 nxtwave disruptive technologies private limited (Hiring for a Client
📍 Bengaluru