Job Title : Tech Lead
Experience : 7–10 Years
Role Overview
We are looking for a Tech Lead – Engineering & AI Projects who can drive the technical vision and execution of both software engineering and AI initiatives. This is a hands-on leadership role that blends strong full-stack engineering capabilities with practical exposure to AI / ML systems, MLOps, and LLM-based applications.
You will lead cross-functional teams, architect scalable solutions, and ensure seamless delivery across product, engineering, and AI teams — while mentoring engineers and fostering a culture of technical excellence and innovation.
Key Responsibilities
- Lead architecture, design, and development of robust, scalable engineering and AI solutions across products and platforms.
- Drive the implementation of AI and LLM-integrated systems, including RAG pipelines and Agentic AI workflows, using frameworks such as LangChain, CrewAI, or LangGraph.
- Architect and oversee cloud-native, microservices-based applications leveraging Node.js, TypeScript, and modern DevOps practices.
- Collaborate with product owners, AI engineers, data teams, and DevOps to align solutions with business goals and delivery timelines.
- Promote best practices in software engineering, AI integration, testing, and observability across teams.
- Mentor and guide engineers, fostering growth, innovation, and technical ownership.
- Conduct technical reviews, performance audits, and ensure delivery of high-quality, maintainable code.
- Evaluate and recommend emerging technologies in AI and modern engineering for adoption.
Experience :
7–10 years of software engineering experience with a strong backend or full-stack foundation.Minimum 2–3 years of AI / ML system delivery experience — designing, deploying, or integrating production-grade models or LLM-based systems.Proven experience leading technical teams, mentoring engineers, and driving delivery across multiple projects.Technical Skills
Strong hands-on expertise in Node.js, TypeScript, and backend frameworks (Fastify, NestJS, or Express).Proficiency in databases (MongoDB, PostgreSQL, or NoSQL systems).Practical experience with LLMs, RAG architectures, and vector databases (Pinecone, FAISS, Chroma).Familiarity with AI / ML frameworks (PyTorch, TensorFlow, Scikit-learn) and MLOps tools (MLflow, Airflow, Kubeflow).Strong understanding of cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).Exposure to frontend frameworks (React, Vue.js) and full-stack delivery practices.Knowledge of DevOps pipelines, CI / CD, and observability tools (Grafana, Prometheus, etc.).Soft Skills
Excellent communication and stakeholder management abilities.Strong analytical mindset and problem-solving orientation.Proven leadership in cross-functional environments with multiple stakeholders.Passion for mentoring, learning, and staying current with evolving AI and engineering practices.Preferred Skills
Experience in AI productization — embedding AI or LLM capabilities into customer-facing products.Understanding of Responsible AI principles and ethical AI usage.Background in consulting or product engineering environments delivering to global clients.Experience managing distributed or hybrid teams.