Senior Software Engineer

Job Description

Roles & Responsibilities:

Role Overview

We are building an AI Factory to deliver intelligent solutions that revolutionize HR processes and business decision-making. The AI/ML Engineer – Full-Stack Capable will be a core builder, responsible for end-to-end design, development, deployment, and scaling of AI/ML applications.

This role blends AI/ML engineering with full-stack software development to ensure our solutions are production-ready, secure, and seamlessly integrated into our HR and enterprise systems.

Responsibilities:

• Collaborate with business analysts, HR domain experts, and data scientists to translate AI concepts into deployable products.

• Design, train, test, and optimize AI/ML models (NLP, predictive analytics, recommendation engines, GenAI, etc.).

• Build full-stack applications to deliver AI capabilities to end users (front-end, back-end, APIs, and database integration).

• Develop data pipelines for preprocessing, feature engineering, and model training using HR and business datasets.

• Deploy AI models into production environments (cloud, containerized, or on-premises) with monitoring and maintenance.

• Ensure scalability, performance, and security of AI applications.

• Integrate with existing HR platforms and enterprise systems.

• Implement MLOps best practices for model lifecycle management, retraining, and versioning.

• Document architecture, code, and processes to ensure maintainability.

• Stay updated on emerging AI frameworks, tools, and compliance requirements (including AI ethics and governance).

Qualifications

Educational qualification:

• Bachelor’s or master’s in computer science, AI/ML, Data Science, or related field.

• Additional certifications in AI/ML or cloud development are an advantage.

Experience:

Overall, 5- 8 years of experience, 3 years of hands-on experience in AI/ML model design, training, and deployment experience for a large-scale application at country or regional or worldwide scale.

Mandatory/requires Skills:

• Programming Languages: Strong in Python (AI/ML), plus JavaScript/TypeScript for full-stack development.

• AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers.

• Front-End Development: React, Angular, or Vue.js.

• Back-End Development: Node.js, Django, or Flask.

• Cloud Platforms: AWS, Azure, or GCP AI/ML services (e.g., Sagemaker, Azure Machine Learning, Vertex AI).

• MLOps Tools: MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines.

• Databases: SQL and NoSQL (e.g., PostgreSQL, MongoDB).

• API Development: REST, GraphQL.

Preferred Skills:

• Experience with Generative AI (LLMs, prompt engineering, fine-tuning).

• Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) for semantic search.

• Knowledge of event-driven architectures and microservices.

• Exposure to HR data structures and people analytics platforms.

• Experience with automated testing for AI pipelines and applications.

• Knowledge of data streaming frameworks (Kafka, Kinesis).

• Open-source contribution or portfolio of AI/ML projects.