Software Engineer

Role Overview: You will collaborate with cross-functional teams to build AI-driven applications for improved productivity and reporting. You will lead integrations with hosted AI solutions (ChatGPT, Claude, Grok) for immediate functionality without transmitting sensitive data while laying the groundwork for a robust in-house AI infrastructure. Additionally, you will develop and maintain on-premises large language model (LLM) solutions (e.g. Llama) to ensure data privacy and secure intellectual property. Key Responsibilities: - LLM Pipeline Ownership: You will set up, fine-tune, and deploy on-prem LLMs; manage data ingestion, cleaning, and maintenance for domain-specific knowledge bases. - Data Governance & Security: You will assist the IT department in implementing role-based access controls, encryption protocols, and best practices to protect sensitive engineering data. - Infrastructure & Tooling: You will oversee hardware/server configurations (or cloud alternatives) for AI workloads; evaluate resource usage and optimize model performance. - Software Development: You will build and maintain internal AI-driven applications and services (e.g., automated report generation, advanced analytics, RAG interfaces, as well as custom desktop applications). - Integration & Automation: You will collaborate with project managers and domain experts to automate routine deliverables (reports, proposals, calculations) and speed up existing workflows. - Best Practices & Documentation: You will define coding standards, maintain technical documentation, and champion CI/CD and DevOps practices for AI software. - Team Support & Training: You will provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and limiting model hallucinations. - Performance Monitoring: You will track AI system metrics (speed, accuracy, utilization) and implement updates or retraining as necessary. Qualification Required: - Bachelors or masters in computer science, Software Engineering, or a related field (or equivalent practical experience). - Proven record of deploying, fine-tuning, or integrating large-scale NLP models or other advanced ML solutions. - Strong proficiency in Python (PyTorch or TensorFlow) and familiarity with MLOps tools (e.g., Airflow, MLflow, Docker). - Understanding of data privacy frameworks, encryption, and secure data handling practices, especially for sensitive internal documents. - Comfortable setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). - Experience working cross-functionally with technical and non-technical teams; ability to clearly communicate complex AI concepts. Please note that the benefits include health insurance, provident fund, yearly bonus, and the work schedule is day shift from Monday to Friday. The work location is in person. The application deadline is 30/06/2025, and the expected start date is 10/06/2025.,