Job Description Position : Senior Software Engineer / Principal Software Engineer - ETL Experience Expected : 4-6 years. Job Description : Designing, developing, and deploying Data Transformation using SQL portion of the data warehousing solution. Definition and implementation of Database development standards, procedures Skills / Competencies: Ability to develop and debug complex and Advance SQL queries, and stored procedures (must have) Hands-on experience in either one or more of the ETL tools like Talend, Informatica (good to have) Hands on experience on any one streaming tool like DMS, Qlik, Golden gate, IICS , Open Flow Hands on experience using snowflake and Postgres databases Database optimization experience would be an added advantage. (good to have) Excellent design, coding, testing, and debugging skills. Should have experience in AGILE methodologies, experience in custom facing will be an added advantage. (good to have) Automation using phyton, java or any other tool will be an added advantage. (good to have)
You are a skilled Generative AI Developer with expertise in Large Language Models (LLMs), prompt engineering, and modern GenAI solution design. You should be proficient in working with Retrieval-Augmented Generation (RAG), Agents frameworks, and AWS Bedrock, with a fundamental understanding of LLMOps practices. Additionally, having proficiency in Streamlit for developing quick front-end prototypes of GenAI applications is highly desirable. Your responsibility will include developing and maintaining GenAI solutions using LLMs, RAG pipelines, and agent-based workflows. You will integrate LLMs into applications using APIs and cloud-based services like AWS Bedrock. It is essential to conduct experiments and research on the latest GenAI advancements and implement proof-of-concepts (PoCs). Collaborating with architects, data engineers, and DevOps teams to build scalable GenAI solutions will also be a part of your role. In terms of technical requirements, you should have a total of 6-8 years of experience with at least 3+ years of hands-on experience in AI/ML or NLP. Hands-on experience with LLMs such as GPT, Claude, LLaMA, Mistral is crucial. Understanding of RAG workflows, experience with vector databases like FAISS, Pinecone, OpenSearch, and exposure to agent frameworks is necessary. Familiarity with AWS Bedrock, prompt orchestration tools, and basic LLMOps practices are also essential. Your expertise in prompt engineering, proficiency in Streamlit, strong programming skills in Python, and experience with REST APIs are required. Preferred skills include exposure to document processing pipelines, unstructured data extraction, knowledge of MLOps, CI/CD tools, and prior experience in integrating GenAI into real-world applications. Soft skills that are important for this role include strong analytical and problem-solving skills, curiosity and initiative in researching new GenAI trends, and good communication and collaboration skills, especially in a cross-functional team environment.,
As a skilled Generative AI Developer with hands-on experience in Large Language Models (LLMs), prompt engineering, and modern GenAI solution design, you will be responsible for building scalable, real-world GenAI applications and continuously exploring advancements in the field of Generative AI. You should be comfortable working with Retrieval-Augmented Generation (RAG), Agents frameworks, and AWS Bedrock, with a basic understanding of LLMOps practices. Proficiency in Streamlit for developing quick front-end prototypes of GenAI applications is highly desirable. **Key Responsibilities:** - Develop and maintain GenAI solutions using LLMs, RAG pipelines, and agent-based workflows. - Integrate LLMs into applications using APIs and cloud-based services like AWS Bedrock. - Conduct experiments and research on the latest GenAI advancements and implement proof-of-concepts (PoCs). - Contribute to LLMOps practices including prompt versioning, testing, and basic monitoring. - Collaborate with architects, data engineers, and DevOps teams to build scalable GenAI solutions. **Technical Requirements:** - 6-8 years of total experience with at least 3+ years of hands-on experience in AI/ML or NLP. - Hands-on experience working with LLMs (e.g., GPT, Claude, LLaMA, Mistral). - Understanding of RAG workflows and experience with vector databases (e.g., FAISS, Pinecone, OpenSearch). - Exposure to agent frameworks like Crewai, LangGraph, Semantic Kernel, or custom orchestrators. - Familiarity with AWS Bedrock and prompt orchestration through tools like LangChain or PromptLayer. - Knowledge of basic LLMOps practices such as prompt versioning, monitoring, and logging. - Proven experience in prompt engineering designing few-shot examples, controlling hallucinations, and optimizing outputs. - Proficient in Streamlit for building lightweight, interactive front-ends. - Strong programming skills in Python and experience with REST APIs. - Good in Deep Learning architectures: RNN, CNN, Transformer-based models. - Experience with NLP using open-source libraries (e.g., spaCy, Hugging Face, NLTK). - Familiarity with data storage and search systems such as PostgreSQL, Elasticsearch, or similar. **Preferred Skills:** - Exposure to document processing pipelines and unstructured data extraction. - Knowledge of MLOps and CI/CD tools (e.g., GitHub Actions, Docker). - Prior experience integrating GenAI into real-world applications. As you embark on this role, your strong analytical and problem-solving skills will be essential in breaking down complex challenges. Your curiosity and initiative in researching new GenAI trends and applying them practically, along with your good communication and collaboration skills, especially in a cross-functional team environment, will contribute to your success in this position.,