Responsibilities
- Build and deploy production LLM-powered AI agents, including voice agents.
- Own the end-to-end AI system lifecycle from problem scoping and design through deployment, monitoring, and iteration.
- Design and optimize prompts, RAG pipelines, and evaluation frameworks to improve accuracy, latency, and reliability.
- Work directly with customers and Implementation Managers to understand workflows, solve problems, and support successful go-lives.
Requirements
- 1–3 years of experience in backend, data, or AI engineering.
- Strong Python and SQL skills.
- Experience or exposure to LLMs, RAG, or prompt engineering.
- Ability to take ownership, work in ambiguity, and ship quickly.
- Comfort working with customers and cross-functional teams.
- Preferred: B.Tech, BE, or M.Tech in Computer Science or a related discipline.
- Bonus: experience with production LLM systems, AI agents, evaluation, agent tooling, voice AI, Databricks, MongoDB, distributed systems, startups, or customer-facing engineering.
Benefits
- In-office work arrangement.
- Opportunity to work on production AI systems rather than demos.
- End-to-end ownership and fast iteration cycles.
- Direct impact on enterprise customers and business outcomes.
Categories
About Prodigal
Prodigal maximizes payments for lenders and debt collectors by building dynamic strategies and motivating consumers with highly engaging, personalized treatments. Our advanced genAI has been trained on over 400 million consumer finance conversations, delivering unmatched industry expertise so you can drive record recovery rates. Experience the power of intelligent debt resolution with Prodigal’s AI that pays. Prodigal is headquartered in Mountain View, California, and our global team is on a mission to build the intelligence layer that powers consumer finance. With the backing of domain experts, technology leaders, and top investors, including Accel, Menlo Ventures, and Y-Combinator, Prodigal is poised to become the next iconic vertical SaaS company.