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Role : SDE 2
Experience: 2+ Years
Location: Mumbai- Andheri East (On-site)
Introduction-
$11 trillion of money flows every year between companies in India. It typically takes avg. 70 days for a business to get paid, and it's increasing 5% every year, leading to a severe credit crunch in the economy. We are building India's first AI-driven Finance & Accounting Company that transforms how businesses pay and get paid.
We are looking for someone who loves a challenge, is ambitious, super tenacious and persistent. S/he is a self-starter, thrives in a dynamic, small start-up environment, has a knack for understanding customer needs, and is result-oriented. If you check these boxes - we want to talk to you!
We are seeking an experienced AI Engineer to join our Engineering Team. The ideal candidate will have deep expertise in Large Language Models (LLMs), OCR, Retrieval Augmented Generation (RAG), and Agentic AI systems, coupled with strong experience in cloud-native, enterprise-scale environments. This role is pivotal in driving our AI innovation strategy, leading end-to-end solution development, and delivering production-grade AI systems.
Key Responsibilities:
● Lead the full lifecycle of Generative AI solutions — from design and development to deployment encompassing LLM-powered workflows, RAG pipelines, OCR, and Agentic AI systems.
● Architect and implement secure, scalable AI infrastructures using GCP, AWS, or Azure.
● Apply LLMOps best practices, including fine-tuning, advanced prompt engineering, and model optimization, to maximize performance and contextual accuracy.
● Design and maintain APIs and microservices (FastAPI, REST, Spring Boot) to integrate AI capabilities into enterprise systems.
● Build and optimize data pipelines and manage vector databases and Elasticsearch for efficient knowledge retrieval and decision-making.
● Implement MLOps, CI/CD, and DevOps pipelines using Kubernetes, Docker, Jenkins, and Ansible for automated deployment and monitoring.
● Ensure system reliability and observability through logging, monitoring, and infrastructure-as-code practices (e.g., ELK stack).
● Collaborate cross-functionally with product, engineering, and business teams to align AI solutions with organizational goals.
● Mentor and guide junior engineers, setting best practices for scalable, maintainable AI development.
Required Experience:
2+ years of professional software engineering experience focused on Generative AI / LLMbased applications.
Proven experience in developing and deploying enterprise-grade AI systems.
Job ID: 149374829
Skills:
Machine Learning, Api Development, Python, AWS, LangChain, vector databases, Anthropic, NLP libraries, LangGraph, LLM orchestration frameworks, Mistral, Llama, OpenAI, LlamaIndex, RAG architectures
Skills:
MLops, Python, Api Development, FAISS, LanGraph, RAG pipelines, LLMs, OpenAI, vector search, SLMs, Hugging Face, embedding models, Weaviate, Anthropic SDKs, LangChain, Pinecone, Generative AI
Skills:
Microservices, Tensorflow, Numpy, Nlp, Pytorch, Python, AWS, Apis, Machine Learning Algorithms, Sql, Deep Learning, Gcp, Pandas, Azure, Model fine-tuning, Hugging Face, MLflow, RAG architectures, LangChain, Generative AI, NoSQL databases, Scikit-learn, cloud platforms, CI CD pipelines, MLOps concepts

Skills:
Retrieval-Augmented Generation (RAG), Sql, Python, Azure, Gcp, Microservices, Tensorflow, Pytorch, AWS, ML Frameworks, Generative AI Concepts, Agentic AI Frameworks, Cloud Platforms, Prompt Engineering, Vector Databases, Pinecone, Weaviate
Skills:
Azure ML, MLops, App Services, Data Lake, Cosmos DB, Azure, Azure DevOps, locust, Key Vault, App Insights, Managed Identity, Log Analytics, K6, Azure AI Foundry, Synapse, GitHub Actions, AIOps
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