Agentic AI and Gen AI Engineer

About the Role: We are looking for an ideal candidate with 5+ years of experience in Data Science / Machine Learning, with strong hands-on experience in Generative AI, Large Language Models (LLMs), NLP, and AI-powered applications. The candidate should be comfortable working across the complete AI lifecycle—from understanding business requirements and experimenting with models to building, evaluating, deploying, and monitoring production-grade GenAI solutions. The role requires a combination of strong technical expertise, business understanding, problem-solving ability, and stakeholder management skills. Key Responsibilities : Generative AI & LLM · Design, develop, and deploy Generative AI and LLM-based solutions for enterprise use cases. · Work with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini , or equivalent LLM platforms. · Develop applications using prompt engineering, structured outputs, function/tool calling, and LLM orchestration. · Design and implement Retrieval-Augmented Generation (RAG) solutions. · Work with vector databases and semantic search for enterprise knowledge retrieval. · Develop and evaluate AI agents and multi-step AI workflows. · Implement techniques such as prompt optimization, context management, grounding, and hallucination reduction. · Develop AI solutions for text classification, summarization, information extraction, question answering, document intelligence, and other enterprise use cases. Machine Learning & Data Science · Develop and optimize traditional Machine Learning and statistical models where appropriate. · Perform data exploration, feature engineering, model selection, training, validation, and evaluation. · Apply appropriate ML and statistical techniques to solve business problems. · Work with structured, unstructured, and semi-structured data. · Develop scalable data pipelines to support AI/ML solutions. · Collaborate with Data Engineers to prepare and manage data for AI applications. AI Evaluation & Productionization · Design evaluation frameworks to measure LLM accuracy, relevance, groundedness, toxicity, latency, and cost. · Implement guardrails and responsible AI practices. · Monitor model and application performance in production. · Identify model/data drift and implement appropriate improvement strategies. · Optimize AI solutions for performance, scalability, reliability, and cost. · Support deployment and productionization of AI/ML solutions. · Client & Delivery Responsibilities · Work closely with the CEO, Delivery team, Solution Architects, Engineering teams, and clients to understand business problems and identify AI opportunities. · Translate business requirements into practical AI/ML solutions. · Participate in client discussions, solution presentations, technical workshops, and POCs. · Develop rapid prototypes and demonstrate the feasibility of GenAI solutions. · Convert successful POCs into scalable, production-ready applications. · Provide technical guidance and contribute to AI solution architecture. · Prepare technical documentation, solution approaches, and project estimates where required. · Stay current with developments in Generative AI, LLMs, Agentic AI, and AI engineering. Required Skills : · 5+ years of hands-on experience in Data Science, Machine Learning, AI, or a related field. · Strong practical experience in Generative AI and LLM-based applications. · Strong proficiency in Python. · Strong understanding of Machine Learning and statistical concepts. · Hands-on experience with: o LLMs o Prompt Engineering o RAG o Vector Databases o Embeddings o Semantic Search o LLM Evaluation o AI Guardrails · Experience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, or equivalent. · Experience with APIs and integrating LLMs into enterprise applications. · Strong SQL and data handling skills. · Experience working with large and complex datasets. · Strong understanding of NLP concepts.XX Technical Skills: · Experience with OpenAI / Azure OpenAI / AWS Bedrock / Google Vertex AI. · Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or equivalent. · Experience with Databricks, Snowflake, or cloud data platforms. · Experience with Docker and CI/CD. · Exposure to AWS, Azure, or GCP. · Experience with ML/AI deployment and MLOps. · Knowledge of AI security, data privacy, governance, and responsible AI. · Experience building AI Agents / Agentic AI workflows. · Experience with multimodal AI is an added advantage Key Competencies · Strong analytical and problem-solving ability. · Ability to translate business problems into practical AI solutions. · Strong communication and presentation skills. · Ability to interact confidently with senior stakeholders and clients. · Strong ownership and delivery mindset. · Ability to work independently in a fast-paced environment. - Strong experimentation and innovation mindset. - Ability to balance technical feasibility, business value, scalability, and cost. Required Education & Experience : · Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering , or a related discipline Skills:- Generative AI and Large Language Models (LLM) tuning