AI Engineer (8 years of experience)

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 :

1. 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).

2. 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.

3. 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.

4. 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.

5. 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 :

- 8 years of full stack software engineering experience.

- Hands-on AI/ML implementation in production environments.

- Strong proficiency in Python (FastAPI, Flask, or Django).

- Strong proficiency in 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.