Full Stack AI Engineer

Do you love a career where you Experience, Grow & Contribute at the same time, while earning at least 10% above the market? If so, we are excited to have bumped onto you.

Learn how we are redefining the meaning of work , and be a part of the team raved by Clients, Job-seekers and Employees.

• Jobseeker Video Testimonials
  
• Employee Glassdoor Reviews
  

If you are a Full Stack AI Engineer looking for excitement, challenge and stability in your work, then you would be glad to come across this page.

We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.

Check if you are up for maximizing your earning/growth potential, leveraging our Disruptive Talent Solution.

Requirements

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.

Key Responsibilities

AI / Machine Learning

• Design and implement AI/ML solutions for real-world business use cases.
  
• Integrate ML models (e.g., forecasting, classification, NLP, 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 & 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 & 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.
  
• 
  

Required Qualifications

• 5+ years of full stack software engineering experience.
  
• 2+ years of hands-on AI/ML implementation in production environments.
  
• Strong proficiency in:
  
• Python (FastAPI, Flask, or Django)
  
• JavaScript/TypeScript (React, Angular, or Vue)
  
• 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 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.
  

Benefits