Full Stack Computer Vision AI Engineer

Overview :

We are seeking a versatile and highly skilled Full Stack AI Platform Engineer to design, develop and deploy intelligent, scalable on prem and cloud-native applications. This role blends frontend and backend development with applied AI engineering and MLOps/DevOps practices. The ideal candidate will have hands-on experience across the stack with a strong understanding of computer vision and generative AI workflows, microservices architecture, real time processing and cloud automation.

Responsibilities :

Frontend Development :

- Build responsive and performant Single Page Applications (SPAs) using React frameworks

- Design intuitive UIs and dashboards that support AI output, including streaming (SSE) and real-time updates.

- Implement real-time video stream rendering and result overlays using SSE/WebSockets.

- Rapidly prototype and iterate on UI concepts in collaboration with clients and stakeholders.

- Utilize modern styling tools like TailwindCSS to enhance development efficiency.

Backend Development :

- Develop scalable backend services using Python and FastAPI, following Microservices Architecture (MSA)

- Build and maintain RESTful APIs and support MCP (Multi-Channel Processing) server/client implementations.

- Apply Test-Driven Development (TDD) and Clean Architecture principles to ensure code quality and maintainability.

Applied AI Computer Vision Engineering :

data preprocessing, training, validation, and inference pipelines

object detection, segmentation, classification, and anomaly detection

model drift detection, auto-retraining triggers, and active learning loops

edge devices and real-time environments (ONNX, TensorRT, OpenCV, NVIDIA Jetson, etc.)

Collaborate with AI/ML teams to embed vision intelligence into platform components and production systems.

DevOps & Cloud Automation :

- Manage containerized deployments using Docker and Kubernetes across edge and cloud environments.

- Support CI/CD pipelines and ensure smooth deployment across environments.

- Operate within AWS, Azure, or other public cloud platforms with a strong understanding of cloud-native services.

Soft Skills :

- Strong problem-solving and analytical thinking.

- Excellent communication and collaboration skills.

- Ability to create and maintain technical documentation

- Ability to work in a fast-paced, agile environment with cross-functional teams.

- Ability to empathize with customer challenges and engage in conversations.

- Defining technical requirements based on business needs and conveying them to customers.

- Effectively communicating complex technical concepts to both technical and non-technical audiences.

- Correctly understanding the feasible requirements and limitations of AI and educating customers.

- Building close relationships with customers and understanding their requirements.

Requirements :

Required Skills :

Frontend:

Backend:

Computer Vision:

MLOps/DevOps:

Preferred Qualifications

real-time defect detection, quality inspection, or video analytics

MLOps frameworks

vector databases or embedding-based retrieval

Contributions to open-source CV projects or a strong portfolio of applied vision systems.

Cloud or DevOps certifications (AWS, Azure, GCP) are a plus.