3-6 Years Noida Responsibilities Drive end-to-end AI application development from idea conception and hypothesis formulation through rigorous testing to production deployment and monitoring ensuring solutions solve real-world problems Embrace a boundaryless approach to technology collaborating across backend systems frontend interfaces where applicable automation scripts and data pipelines to deliver holistic solutions Design implement and meticulously fine-tune LLM prompts embeddings RAG pipelines and sophisticated AI agents using frameworks like Langchain CrewAI Bedrock Agents OpenAI SDK Autogen etc tailored to specific domain use cases and business objectives Architect and build Generative AI solutions that are inherently scalable secure cost-efficient and privacy-conscious integrating these considerations from the initial design phase Implement robust testing methodologies and MLOps practices specifically for GenAI focusing on preventing prompt drift mitigating hallucinations ensuring model regression testing and maintaining high performance Maintain exceptionally high standards in code hygiene implement robust CI CD practices for AI models and applications and produce clear comprehensive documentation Collaborate closely with data analysts and engineers to guarantee data quality readiness and the efficiency of data pipelines feeding into GenAI models and applications Formulate and validate hypotheses by engaging directly with stakeholders understanding their needs deeply and translating them into actionable technical requirements Champion rapid prototyping and lean experimentation methodologies build fast fail fast learn faster and iterate quickly to test ideas before committing significant resources Engage proactively and cross-functionally with Product Management Design Business Analysts Security and Legal teams to navigate complex requirements and deliver impactful solutions Actively contribute to a vibrant culture of learning and innovation by creating tech blogs developing internal Proofs-of-Concept POCs delivering demos and conducting workshops on GenAI topics Stay relentlessly current with the rapidly evolving Generative AI landscape including new trends models tools like AWS Bedrock Azure OpenAI Vertex AI and research advancements critically evaluating opportunities for integration and improvement Provide technical leadership and mentorship to junior engineers fostering a culture of technical excellence and continuous learning within the GenAI space Requirements A minimum of 1 years of Data Science experience demonstrating strong expertise in building robust AI ML systems and scalable application architectures At least 2 years of focused hands-on experience building and deploying practical Generative AI applications such as AI virtual assistants complex AI agents and content generation tools Managed and delivered solutions for X clients contributing to Y in revenue and ensuring high client satisfaction across multiple verticals Spearheaded initiatives that improved operational efficiency and scalability leading to measurable gains in revenue growth and client acquisition Proven experience utilizing core GenAI tools and platforms like AWS Bedrock including various foundation models and Bedrock Agents LangChain designing and implementing RAG pipelines leveraging Agent-based frameworks e g CrewAI working with vector databases e g Pinecone Weaviate Qdrant Milvus ChromaDB and understanding LLM principles Experience with model training fine-tuning e g LoRA QLoRA and core NLP concepts is essential High proficiency in Python and robust familiarity with modern ML AI libraries e g Hugging Face Transformers PyTorch TensorFlow Scikit-learn Pandas NumPy and relevant SDKs e g Boto3 OpenAI SDK Demonstrated practical experience in developing performance tuning and optimizing LLM-based applications including sophisticated prompt engineering techniques Experience leveraging AI coding assistants e g GitHub Copilot Amazon Q Cursor to accelerate development workflows while maintaining code quality Deep understanding and practical application of data privacy principles security best practices and cost-aware system design specifically within the context of AI and Generative AI applications Strong understanding of working effectively with both structured and unstructured data including efficient retrieval processing and transformation techniques for GenAI Proven ability to work effectively across diverse disciplines collaborating seamlessly with product design business and other engineering teams in fast-paced dynamic environments Hands-on experience developing and deploying applications on cloud platforms with AWS being highly preferred Excellent analytical and problem-solving skills coupled with a strong bias toward action experimentation and continuous learning Exceptional communication and collaboration skills capable of articulating complex technical concepts clearly to various audiences What sets you apart Active contributions to relevant open-source GenAI tools or frameworks e g LangChain LlamaIndex Hugging Face A strong portfolio showcasing personal AI side projects or significant contributions to GenAI initiatives Exposure to frontend technologies e g React Streamlit Gradio and the ability to contribute across the full stack for end-to-end feature ownership Experience with other cloud platforms GenAI offerings e g Azure OpenAI Google Vertex AI Familiarity with advanced MLOps tools and practices tailored for LLMs

📌 Senior Software Engineer - Data Science (Uttar Pradesh)
🏢 To The New
📍 Uttar Pradesh