GEN AI Lead / Chartered Engineer

Job description

Banglalink is looking for a GEN AI Lead / Chartered Engineer to define the architecture, standards and engineering direction of its enterprise Generative AI platforms and applications. The role covers scalable, secure and cost-efficient GenAI platforms and reusable AI services, leads development of enterprise AI copilots, conversational BI, customer-service assistants, recommendation engines and autonomous workflow agents, and mentors ML and GenAI engineers across the AI Excellence Team while partnering with business leaders.

Responsibilities

• Define the architecture, standards and engineering direction of enterprise Generative AI platforms and applications
• Architect scalable, secure and cost-efficient enterprise GenAI platforms, AI infrastructure and reusable AI services
• Establish standards and best practices for LLMOps, RAG pipelines, agent orchestration, prompt management, AI governance, model evaluation and AI observability
• Lead development of enterprise AI copilots, conversational BI systems, AI-powered customer service assistants, recommendation and personalization engines, knowledge retrieval systems and autonomous workflow agents
• Build advanced orchestration workflows involving multiple AI agents and tools, and drive production deployment and scaling of GenAI systems
• Mentor ML and GenAI engineers across the AI Excellence Team and partner with business leaders to turn high-impact opportunities into scalable AI solutions
• Evaluate emerging GenAI technologies, models and frameworks, and influence enterprise AI strategy, governance and roadmap
• Lead performance optimization for latency, throughput, GPU utilization, inference cost and reliability, while ensuring compliance with security, privacy and responsible AI standards

Requirements

• Bachelor's or Master's degree in Computer Science, Applied Statistics, Business or a relevant field
• 4-7 years of experience in AI/ML engineering, software engineering, distributed systems and enterprise AI platforms, with proven experience building and deploying large-scale AI/GenAI systems in production
• Strong expertise in Python and backend engineering, with the ability to architect distributed systems and operationalize production-scale GenAI applications
• Strong hands-on experience with LLM application development, prompt engineering frameworks, RAG architectures, AI agents and tool-calling systems, semantic search and embeddings, AI evaluation and guardrails, hallucination mitigation, and context/memory management
• Experience with GenAI frameworks and tools such as LangChain, LlamaIndex, FastAPI, Docker, Kubernetes, MLflow, and CI/CD and DevOps workflows
• Experience with AI infrastructure including GPU-based inference systems, open-source LLM deployment, fine-tuning techniques (LoRA/PEFT), vector databases, distributed AI workloads and cloud-native architectures
• Hands-on familiarity with major cloud platforms (Amazon Web Services, Google Cloud, Microsoft Azure)
• Experience leading technical teams or AI engineering squads, with exposure to AI governance, responsible AI and enterprise compliance frameworks
• Strong stakeholder influence, business communication and presentation skills

Skills

• Cloud Computing
• Docker
• FastAPI
• Generative AI
• Kubernetes
• LangChain
• LlamaIndex
• LLMOps
• MLflow
• Python
• RAG
• Vector Databases