Artificial Intelligence Engineer

Role –AI Engineers & Senior AI Engineers

Roles and Responsibilities:

2 – 6 years of product development experience for large scale systems with high volume and high-performance requirements.

AI Engineer with a blend of AI deployment, MLOps, software integration, and AI infrastructure skills, the ideal candidate should have:

1. Strong AI/ML Engineering Skills

o Hands-on experience in model deployment, integration, optimization, and serving AI models in production.

o Ability to integrate AI models into lending workflows and APIs.

o Expertise in LLM prompt engineering, calling tools, RAG, and structured outputs

2. ML Ops & Cloud Deployment Expertise

o Knowledge of CI/CD pipelines for AI models.

o Knowledge in containerization (Docker, Kubernetes).

o Knowledge of security and compliance

o Knowledge of cloud-based AI services (AWS).

3. AI Software & API Integration

o Expert in Python / TypeScript programming

o Building APIs to serve AI models in real-time decision-making for lending and risk assessment.

o Experience with serverless AI architectures and event-driven workflows.

o Experience with Vector DB and RDBMS / NoSQL

4. AI Infrastructure & Scaling

o Knowledge of AI workloads efficiently, optimizing for low latency and high availability.

o Experience with GPU acceleration and distributed computing frameworks.

Desired Candidate Profile-

· Preferably from a product-based company.

· Minimum 60% throughout academics, including highest qualification.

· Strong programming skills in Python / TypeScript, and API development.

· Hands-on experience with MLOps tools, containerization, and cloud platforms.

· Knowledge of AI model deployment, scaling, and performance optimization