Senior Backend Engineer (Gen-AI) at Prodapt

Prodapt is the largest and fastest-growing specialized player in the Connectedness industry, recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider across North America, Europe and Latin America. With its singular focus on the domain, Prodapt has built deep expertise in the most transformative technologies that connect our world. Prodapt is a trusted partner for enterprises across all layers of the Connectedness vertical. Prodapt designs, configures, and operates solutions across their digital landscape, network infrastructure, and business operations – and craft experiences that delight their customers. Today, Prodapt’s clients connect 1.1 billion people and 5.4 billion devices, and are among the largest telecom, media, and internet firms in the world. Prodapt works with Google, Amazon, Verizon, Vodafone, Liberty Global, Liberty Latin America, Claro, Lumen, Windstream, Rogers, Telus, KPN, Virgin Media, British Telecom, Deutsche Telekom, Adtran, Samsung, and many more. A “Great Place To Work® Certified™” company, Prodapt employs over 6,000 technology and domain experts in 30+ countries across North America, Latin America, Europe, Africa, and Asia. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 30,000 people across 80+ locations globally.

We are seeking Senior backend dev Engineers to join our team, working with a leading FinTech client to develop innovative AI solutions. Our client is building a GenAI Developer Assistant—an end-to-end GenAI-driven SDLC assistant framework. This platform leverages advanced GenAI technologies to accelerate product development and deployment, fostering innovation and delivering services to customers swiftly.  

Roles & Responsibilities: The Senior backend dev Engineer focuses on fine-tuning and optimizing large language models to meet the customer’s SDLC requirements, ensuring relevant outputs for tasks like code suggestions and documentation. Optimize model performance for specific use cases and integrate LLMs into SDLC workflows. The role involves managing vector and graph databases to support efficient data retrieval in the GenAI pipeline, designing and maintaining database structures, and optimizing query performance for the RAG pipeline. Additionally, work closely with AI engineers to align data needs with model performance and implement strategies for scaling the database systems to support growth.

Qualifications, Education, Certifications and/or Other Professional Credentials • 7+ years in Python, Java or equivalent programming languages • 4+ years on cloud providers such as Azure/GCP/AWS • 3+ years of experience building GenAI services & platforms e.g. adapting models, build RAG pipelines • 3+ years of experience and familiarity with AI/ML Frameworks such as Pytorch/Tensor flow • At least 3 Realtime Gen AI project implementation in following areas o Dev Assistance [ Code generator, Test generator etc.] o RAG pipeline end to end understanding and implementation. o Graph or any retrieval method is added advantage. o At least 2 years of experience, where integrating with various LLM models has done successfully. • Build services using FASTAPI/Flask/Django • 3+ years’ experience working with a wide variety of backend data systems such as Big Q, snowflake having experience in data extraction experience in o streaming platform like kafka, o building data pipelines, o preparing data sets • 3+ Years of experience with DevSecOps flows leveraging technologies such as Git, Jenkins, Docker containers, Kubernetes, EKS and AKS, Datadog Prometheus • 7+ years of experience in IT, preferably at least 2 years in cloud • Certifications by cloud providers- GCP is preferred. (certificate in BigQ, Vertex AI is an added advantage) • Experience writing Libraries and Tools Good to Have Tools: • Testing Frameworks: pytest, JUnit (for testing integrations). • Version Control: Git (to manage SDLC workflow integration). • Collaboration Tools: Slack, Jira (for communication and project tracking). • Multi-Agent Frameworks: Experience with frameworks that support multi-agent coordination and interactions.