Description

AI Engineer

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 solid 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 ResponsibilitiesAI / 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

- 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)

- 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.

📌 AI Engineer (Bengaluru)
🏢 FORNAX TECHNOLOGY SERVICES PRIVATE
📍 Bengaluru