AI Agent Engineer

Job Title: AI Agent Engineer Role Overview :- You will work closely with the Tech Lead to design, build, test, and maintain AI agents for US-based clients. This is a hands-on engineering role where you will write Python code daily, deploy solutions quickly, and take ownership of performance, monitoring, and continuous improvement. As the company scales, you will have the opportunity to lead client engagements within 12–18 months. Key Responsibilities Build and deploy AI agent workflows in Python using Claude API under Tech Lead guidance Integrate AI agents with client systems such as insurance platforms, HR systems, and financial databases Monitor live agents daily and proactively resolve issues before impacting clients Develop performance dashboards to track and report agent activity and outcomes Test edge cases thoroughly (e.g., missing data, API failures, unexpected inputs) Continuously improve prompts and workflows as client data evolves Ensure high reliability, accuracy, and performance of deployed solutions Required Qualifications 3+ years of hands-on experience in Python development Experience working with REST APIs (integration, error handling, response management) Basic understanding of LLMs (prompts, responses, context handling) Experience with cloud platforms (any cloud provider) Strong problem-solving skills with attention to detail Ability to learn by building and experimenting Preferred Skills (Good to Have) Experience with LangChain or similar LLM frameworks (including personal projects) Familiarity with logging, monitoring, and alerting systems Exposure to domains like insurance, HR tech, or financial services Experience building or deploying AI/ML-based applications Ideal Candidate Profile Curious about AI and actively experiments with tools like Claude or LLMs Focused on code quality and real-world performance, not just execution Comfortable working in a fast-paced, ownership-driven environment Values visibility, impact, and growth in their role Growth Path Opportunity to lead client-facing AI projects within 12–18 months Increased ownership of architecture, delivery, and client engagement