AI ENGINEER
Position Summary
Design, develop, deploy, and support AI-powered solutions, including Generative AI applications, Intelligent Assistants, Knowledge Retrieval Systems, Intelligent Automation, and AI-enabled business solutions. Work across diverse technologies and platforms to deliver scalable, secure, and business-driven AI capabilities.
Key Responsibilities
Design, develop, and enhance AI capabilities that address business challenges and deliver measurable business value.
Build AI/GenAI solutions, intelligent assistants, knowledge retrieval systems, AI agents, and AI-powered automation.
Implement Retrieval-Augmented Generation (RAG), prompt engineering, and system integrations.
Evaluate, prototype, and implement appropriate AI models, platforms, and technologies based on business requirements and architectural standards.
Design scalable, secure, and reusable AI architectures and frameworks to accelerate enterprise AI adoption.
Manage deployment, monitoring, performance optimization, and AI lifecycle operations.
Collaborate with business, data, risk, and technology teams to deliver AI solutions.
Ensure security, governance, privacy, and Responsible AI compliance.
Qualifications
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
3-8 years of experience in Software Engineering, AI/ML, Data Engineering, Cloud Technologies, or Digital Solution Development.
Experience delivering AI-powered applications, automation solutions, or advanced analytics solutions.
Strong problem-solving, stakeholder management, and communication skills.
Technical Skills
Programming: Python, SQL, APIs
AI/ML Development and Generative AI
Large Language Models (LLMs) and Small Language Models (SLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Vector Databases and Semantic Search
Unstructured Data Processing and Data Integration
AI Agents and Agent-Based Architectures
MLOps / LLMOps
CI/CD and Containerization
Cloud, Hybrid, and On-Premises Architectures
AI Security, Governance, and Responsible AI
Preferred Qualifications
Proven experience designing and implementing Retrieval-Augmented Generation (RAG) solutions, including embeddings, vector databases, semantic search, and enterprise knowledge retrieval architectures.
Experience working with AI platforms, foundation models, orchestration frameworks, and AI development tools.
Strong understanding of prompt engineering, AI application development, and agent-based architectures.
Proven ability to design and deliver AI capabilities that address business needs and create measurable business value.
Experience evaluating and selecting appropriate AI technologies, models, and architectures based on business and technical requirements.