AI Technical Lead (TK60FT RM 4325)

Position: AI Technical Lead (TK60FT RM 4325)

Virtual Interviews on 14 & 15-Aug-26

The role requires a functional System Engineer (Business Analyst) mindset

Role Overview
We are seeking an accomplished AI Technical Lead with 6+ years of experience in designing, developing, and deploying enterprise-grade AI solutions. The ideal candidate will lead initiatives around multi-agent systems, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), fine-tuning, context engineering, and AI-driven operations (AIOps). This role requires strong technical leadership, hands-on development skills, and the ability to architect scalable AI platforms that integrate seamlessly with data pipelines and knowledge graphs (Neo4J or similar).

Key Responsibilities

• AI Architecture & Leadership
  o Design and implement multi-agent AI systems for enterprise workflows.
  o Develop and optimize RAG pipelines for knowledge retrieval and contextual reasoning.
  o Integrate MCP for tool and API interoperability across AI agents.
  o Apply context engineering to improve agent reasoning and reliability.
• Model Development
  o Fine-tune LLMs and transformer-based models for domain-specific tasks and enterprise use cases.
  o Evaluate trade-offs between fine-tuning, prompt engineering, and RAG for optimal performance.
  o Collaborate with data scientists to design custom embeddings and model adaptations.
• Data & Knowledge Engineering
  o Build and manage data pipelines for ingestion, transformation, and retrieval.
  o Design and maintain knowledge graphs using Neo4J or similar graph databases to support semantic search and contextual reasoning.
  o Integrate knowledge graphs with RAG pipelines for enhanced retrieval.
• Development & Deployment
  o Lead development using Python (LangChain, HuggingFace, LangGraph, Google ADK, Microsoft Agent Framework etc.).
  o Collaborate with front-end teams using ReactJS (nice to have) for AI dashboards and agent interaction UIs.
  o Ensure scalability, observability, and reliability of AI systems using AIOps practices.
• Leadership & Collaboration
  o Mentor and guide engineering teams in AI best practices.
  o Collaborate with product managers, data scientists, and stakeholders to align AI solutions with business goals.
  o Drive innovation by evaluating emerging AI technologies and frameworks.

Required Skills & Experience

• 6+ years of experience in enterprise AI development.
• Strong expertise in:
  o Multi-agent systems and orchestration frameworks.
  o RAG (Retrieval-Augmented Generation).
  o MCP (Model Context Protocol).
  o Fine-tuning LLMs (HuggingFace, OpenAI fine-tuning, LoRA, PEFT).
  o Context Engineering for LLMs and AI agents.
  o Python for AI pipelines and orchestration.
• Experience with:
  o Data pipelines and ETL workflows.
  o Knowledge graph creation using Neo4J or similar.
  o AIOps for monitoring and deployment of AI systems.
• Exposure to ReactJS for UI development (nice to have).
• Proven track record of leading technical teams and delivering enterprise-grade AI solutions.

Preferred Qualifications

• Experience with cloud-native AI deployments (Azure).
• Knowledge of vector databases (PGVector, Pinecone, Milvus etc).
• Familiarity with DevOps/MLOps practices.
• Strong communication and leadership skills.

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