AI Agent Engineer / LLM Application Engineer

Core Competencies:

Dependability. Follows instructions, responds to management direction; results oriented and committed to achieving objectives and tasks as required.

Teamwork and Collaboration. Exhibits objectivity and openness to others views; Gives and welcomes feedback; Contributes to building a positive culture. Communicates effectively.

Professionalism. approaches others in a tactful manner; Reacts well under pressure; Treats others with respect and consideration; Accountable of all actions and decisions.

Organizational Support. Follows policies and procedures; Completes administrative tasks correctly and on time; Supports organization’s goals and values.

Quality Management. Looks for ways to improve and promote quality; Demonstrates accuracy and thoroughness.

Decision Making. Analyzes each situation, looking for opportunities to make any situation more beneficial for the company. Participates effectively in communication to achieve optimum results.

Tasks Required:

Design, develop, and deploy AI agents and LLM-powered applications for various business use cases
Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval and contextual responses
Develop NLP-based systems for text processing, classification, and conversational AI
Integrate Voice AI systems for speech recognition, voice assistants, and automated call workflows
Connect LLM applications with databases, APIs, and external systems
Fine-tune prompts, optimize model performance, and improve response accuracy
Implement automation workflows using AI agents and orchestration frameworks
Monitor, test, and continuously improve AI system performance and reliability
Document AI architectures, workflows, and deployment processes
Collaborate with cross-functional teams to translate business requirements into AI-driven

Requirements:

Proven experience building LLM-powered applications or AI agents
Strong experience with Retrieval-Augmented Generation (RAG) architectures
Solid background in Natural Language Processing (NLP)
Experience developing Voice AI systems or conversational AI solutions
Proficiency in Python and working with AI/ML frameworks
Experience with LLM APIs (e.g., OpenAI, Anthropic, or similar platforms)
Familiarity with vector databases, embeddings, and semantic search
Experience integrating AI solutions with APIs, databases, and cloud services
Strong analytical and problem-solving skills
Ability to work independently and communicate technical concepts clearly