QBrainX - AI Technology Lead - LLM/RAG/NLP

Job Title :
AI Technology Lead

Experience Level :
10 to 15 years overall; 3+ years in AI leadership

Job Location :
Onsite Hybrid - Coimbatore ODC - India

Reports To :
Head of AI Practice/Director of Delivery

Role Overview
The AI Technology Lead will be responsible for leading a multi-disciplinary team (2040 members) delivering end-to-end AI, Data Engineering, and Digital Transformation solutions for global enterprise clients. This role combines deep technical expertise with delivery leadership to guide solution architecture, mentor engineers, ensure technical excellence, and drive innovation across Generative AI, Agentic AI, and Data ecosystems. Additionally, the role will provide pre-sales support with sales pursuit teams.

Key Responsibilities
Technical Leadership :

• Define and oversee the design and implementation of scalable AI, Data, and Application solutions.
• Engage with onsite Lead Architect & provide architectural and hands-on guidance to offshore leads teams across AI/ML pipelines, data engineering workflows, and application integration layers.
• Lead innovation in Generative AI and Agentic AI, enabling practical business outcomes using LLMs, agents, and cognitive systems.
• Ensure robust MLOps, DataOps, and DevOps practices for production-grade deployments.
• Partner with CoE teams to develop accelerators, reusable components, and proof of-concepts.

Delivery Ownership

• Lead and mentor a cross-functional team including team leads, AI Engineers, Data Engineers, ML Developers, Data Modelers, and Application Developers.
• Ensure timely, high-quality delivery across multiple concurrent client projects.
• Collaborate closely with Solution Architects and Project Managers for technical scope definition, estimation, and execution.
• Conduct periodic code and architecture reviews to maintain quality and performance standards as governed by the Technical Review Board.

Innovation & Advisory

• Evaluate and introduce emerging technologies in AI, GenAI, and cloud data ecosystems (e.g., Snowflake, Databricks, Azure, GCP).
• Contribute to AI-driven solution frameworks and domain-specific accelerators.
• Support client advisory discussions on AI roadmaps, data modernization, and intelligent automation.
• Drive internal upskilling and competency development across the AI and Data teams.

Collaboration & Leadership

• Act as the primary technical authority in delivery engagements & proof-of-concept efforts.
• Work with product owners and business stakeholders to translate business goals into technical outcomes.
• Foster a culture of experimentation, collaboration, and continuous improvement.

Required Skills & Experience

• Strong foundation in AI/ML : including classical ML, NLP, computer vision, and GenAI (LLMs, RAG, prompt engineering, agents).
• Hands-on experience in AI frameworks : PyTorch, TensorFlow, LangChain, LlamaIndex, OpenAI APIs, Hugging Face.
• Expertise in Data Engineering : Spark, Snowflake, Databricks, Azure Data Factory, or similar.
• Cloud experience : GCP (certifications preferred), Azure & AWS.
• MLOps & Deployment : CI/CD for ML models, containerization (Docker/Kubernetes), and monitoring.
• Application integration : working knowledge of API-driven and event-driven architectures.
• Team management : experience leading large technical teams in distributed environments.
• Strong communication and stakeholder management skills.
• Prior consulting or IT services background preferred.

Education

• Bachelors or Masters degree in Computer Science, Engineering, or related field.
• Certifications in AI/ML, Cloud, or Data Architecture preferred.

Success Indicators

• High team utilization and delivery quality across all engagements.
• Accelerated adoption of AI and automation in client solutions.
• Reduced rework and improved delivery velocity through reusable assets and frameworks.
• Growth in team capability through mentoring and structured learning programs.

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