Intelligent Machines

Career/AI Engineers

AI Engineer

AI Engineers

Onsite

Permanent & Full-time (Augmented resources for bKash)

About the roleIntelligent Machines Limited is a technology-driven company focused on building data-powered products and enterprise solutions that create measurable business impact. We combine strategy, design, and engineering to deliver scalable digital experiences across industries.We are seeking a highly skilled AI Engineer to drive the development of production-grade AI systems. In this role, you will bridge the gap between research and production, building everything from Agentic RAG workflows to Computer Vision solutions. You will be responsible for architecting scalable microservices, managing MLOps infrastructure, and mentoring a team of engineers to deliver cutting-edge AI products. If you have a track record with AI agents, managing Kubernetes clusters, and optimizing complex deep learning models, we want to meet you.

Key Responsibilities

Generative AI & LLM Development

01Design and deploy Agentic RAG (Retrieval-Augmented Generation) systems using frameworks like LangChain and LangGraph

02Develop conversational chatbots and coding agents capable of executing complex SQL queries, data analysis, and code generation (using models like GPT-4o, Claude, or Llama)

03Implement observability for LLM applications using tools like Langfuse or similar

Computer Vision & Deep Learning

04Build and fine-tune state-of-the-art models for tasks such as Optical Character Recognition (OCR), Handwriting Recognition (HTR), and Object Detection

05Optimize model performance and implement advanced image processing techniques

MLOps & Infrastructure

06Architect and maintain scalable microservices on cloud platforms (AWS or Azure)

07Manage container orchestration using Kubernetes (EKS/AKS), including Cluster Autoscalers and Horizontal Pod Autoscalers (KEDA)

08Build automated CI/CD pipelines (GitHub Actions/Jenkins) and data pipelines using Apache Airflow

Deployment & Monitoring

09Develop inference pipelines supporting both batch and near real-time processing (Celery, RabbitMQ, FastAPI)

10Set up comprehensive logging and monitoring stacks (Prometheus, Grafana, CloudWatch, Azure Monitor) to track model drift and system health

Leadership & Strategy

11Collaborate with stakeholders to define AI strategy and technical roadmaps

12Mentor junior engineers, conduct code reviews, and oversee tech stack optimization

Required Skills & Experience

—B.Sc. in Computer Science, Engineering, or related field

—4–6 years of relevant professional experience

—Expert-level proficiency in Python

—Strong hands-on experience with PyTorch, TensorFlow, Scikit-Learn, and the Hugging Face ecosystem

—Proven experience with LangChain, vector databases, and prompt engineering

—Solid experience with Docker, Kubernetes, Helm, and at least one major cloud provider (AWS, Azure, or GCP)

—Experience building APIs with FastAPI, Django, or Flask

Preferred Skills

—Experience with LangGraph or other agent-orchestration frameworks

—Experience with LLM observability tooling (Langfuse or similar)

—Familiarity with Celery/RabbitMQ-based inference pipelines

—Experience with Apache Airflow or similar workflow orchestration tools

Nice-to-Have Skills

—Experience mentoring or leading a small engineering team

—Exposure to KEDA-based autoscaling and cost optimization on Kubernetes

—Experience with computer vision fine-tuning for OCR/HTR use cases

SalaryBDT 130K–160K (Based on experience and expertise)

TeamAI Engineers

LocationOnsite

Experience4–6 Years in relevant experience

Employment TypePermanent & Full-time (Augmented resources for bKash)

Reports toHead of AI

SalaryBDT 130K–160K (Based on experience and expertise)

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