- Location
- Mumbai · Mumbai, Maharashtra, India
- Department
- Engineering
- Education
- Bachelor
- Source
- Greenhouse
Description
At Prodigal, we are building AI Agents for loan servicing and collections. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades. We are backed by Y Combinator, Accel and Menlo Ventures.
Today, we stand at the forefront of a seismic shift in the industry, building Agentic AI applications for consumer finance. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine (PIE), we’re creating the next-generation agentic workforce - one that empowers companies to achieve unprecedented levels of operational excellence and intelligence.
With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build Agentic AI applications that will revolutionize the future of consumer finance.
At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.
About the Role -
As a Solution Engineer at Prodigal, you will be building AI solutions for enterprise customers incl. AI agents, NLP models, and automating workflows to enhance efficiency. You’ll work with Python, PySpark, SQL, and Shell scripting, leveraging NLP techniques & LLMs for entity recognition. Additionally, you'll play a crucial role in customer onboarding, collaborating with the Customer Success team to ensure seamless implementation of Prodigal’s solutions for the new customers.
Key Responsibilities -
AI Implementation:
- Build AI agents incl. voice AI agents (prompt engineering, testing, iterating, repeat)
- Apply NLP techniques and LLMs for entity recognition, including pattern-based approaches
- Benchmark NLP models using LLMs to optimize accuracy and performance.
Process Automation & Internal Tooling:
- Develop internal tools to optimize existing processes and workflows.
- Automate Python notebooks and scripts using shell scripting for efficiency.
Customer Onboarding & Implementation:
- Assist in onboarding new customers across all Prodigal products.
- Collaborate with Implementation Managers (IMs) and Customer Success Managers (CSMs) to ensure successful go-live execution
System & Application Monitoring:
-
- Ensure 99.9% uptime for critical systems and application services by proactively monitoring key subsystems (e.g., data ingestion and publishing pipelines).
- Identify, report, and prioritize bug resolution while proposing robust, scalable solutions.
Preferred Qualification -
B.Tech, BE, or M.Tech in Computer Science or a related discipline, with 1-2 years of relevant experience.
Technical Skills -
- Strong proficiency in Python scripting and PySpark.
- Expertise in writing complex SQL queries.
- Experience in automation scripting using Shell
- Familiarity with MongoDB databases and Databricks tables.
- Hands-on experience with version control tools (e.g., Git).
- Exposure to GenAI tools, LLMs, and RAG-based applications.
- Work experience in a fast pace start-up is a plus
Mode of Work - In-Office
From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.
To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
