Key Skills: LLM, ML, AI Engineering, Prompt Engineering

Roles and Responsibilities:

- Design and build production AI systems for healthcare documentation, medical coding, denial management, appeals, and revenue cycle workflows.
- Develop and improve LLM-based systems and supervised machine learning solutions for complex, real-world use cases.
- Establish evaluation and feedback approaches using expert review, production outputs, and benchmarks to measure quality, reliability, and business impact.
- Analyze system failures and operational results, then make evidence-based improvements to model behavior and system design.
- Provide technical direction, review designs, and mentor engineers while coordinating with research, product, ML engineering, and platform teams.

Skills Required:

- 6-9 years of total experience, including at least 5 years in applied AI, machine learning, research engineering, or software engineering.




- Practical experience applying machine learning, including supervised ML models, to production problems.
- Experience building or integrating LLM systems and converting model capabilities into reliable application behavior.
- Strong applied AI engineering and software engineering skills, with a track record of shipping production systems.
- Ability to evaluate AI system quality, investigate failures, and improve outcomes using measurable evidence.

Positive to Have:
- Prompt engineering experience for LLM-based applications.
- Experience in healthcare, revenue cycle management, or another regulated industry.

Education: B.E. or B.Tech in any branch; equivalent practical experience may be considered.

📌 Senior, AI Engineer (Bengaluru)
🏢 MyCareernet
📍 Bengaluru