Full Stack Engineer - AI

We are seeking a highly skilled Full-Stack AI Engineer to design, build, and scale intelligent applications across the full technology stack. This role combines strong backend and frontend engineering expertise with applied AI/ML implementation in enterprise cloud environments. You will work closely with product managers, architects, data scientists, and DevOps teams to deliver production-grade AI-powered solutions that are secure, scalable, and aligned with business objectives. This is a hands-on engineering role requiring experience across application development, AI model integration, cloud architecture, and DevSecOps practices.

The core responsibilities for the job include the following:

AI / Machine Learning:

• Design and implement AI/ML solutions for real-world business use cases.
• Integrate ML models (e. g., forecasting, classification, NLP, and computer vision) into production-grade applications.
• Develop APIs and services that expose AI capabilities securely and efficiently.
• Optimize model performance, latency, scalability, and monitoring in production.
• Implement model lifecycle management (training, deployment, monitoring, retraining).

Backend Development:

• Design and develop scalable RESTful and/or GraphQL APIs.
• Build microservices-based architectures.
• Implement authentication, authorization, and secure API access.
• Develop data pipelines and integrate with structured and unstructured data sources.
• Ensure high availability, performance tuning, and observability.

Frontend Development:

• Develop responsive, user-friendly web applications.
• Build interactive dashboards and AI-driven user experiences.
• Integrate frontend applications with backend AI services.
• Ensure accessibility, usability, and performance optimization.

Cloud and DevOps:

• Deploy applications and models in cloud environments (Azure, AWS, or GCP).
• Implement CI/CD pipelines for application and model deployment.
• Apply infrastructure-as-code (Terraform, ARM, Bicep, etc. ).
• Implement monitoring, logging, and alerting.
• Ensure security compliance and enterprise-grade governance.

Architecture and Collaboration:

• Participate in solution architecture and design discussions.
• Translate business requirements into technical solutions.
• Collaborate with cross-functional teams (product, security, data, UX).
• Contribute to technical standards, best practices, and code reviews.

Requirements:

• 8 years of full-stack software engineering experience.
• Hands-on AI/ML implementation in production environments.
• Strong proficiency in Python (FastAPI, Flask, or Django), JavaScript/TypeScript (React, Angular, or Vue), and REST API development. Experience with ML frameworks (e. g., scikit-learn, PyTorch, TensorFlow, or equivalent).
• Experience deploying AI workloads in cloud environments (Azure ML, SageMaker, Vertex AI, etc. ).
• Experience with relational and NoSQL databases.
• Strong understanding of software engineering principles and design patterns.
• Experience with Docker and container orchestration (Kubernetes preferred).
• Knowledge of secure coding practices and enterprise security standards.

Preferred Qualifications:

• Experience with enterprise AI governance and responsible AI frameworks.
• Experience with MLOps and model monitoring tools.
• Knowledge of distributed systems and event-driven architectures.
• Experience with vector databases and semantic search (if applicable to the organization).
• Experience in regulated industries (financial services, healthcare, public sector).
• Experience working in Agile/Scrum teams.

Key Competencies:

• Strong problem-solving and analytical skills.
• Ability to translate complex AI concepts into scalable technical solutions.
• Excellent communication and stakeholder engagement skills.
• Ownership mindset with the ability to operate independently.
• Strong attention to performance, security, and maintainability.