Role Overview
We are looking for an experienced GenAI / AI-ML Engineer with strong hands-on expertise in Python, machine learning, deep learning, Large Language Models, Retrieval-Augmented Generation, and agentic AI systems. The selected candidate will be responsible for designing, developing, and deploying scalable AI-powered applications. The role requires practical experience in building production-ready RAG pipelines, LLM-powered applications, REST APIs, machine-learning models, and cloud-based AI solutions using AWS.
Key Responsibilities
● Design, develop, test, and deploy scalable AI, machine-learning, deep-learning, and Generative AI solutions. ● Build and optimise Retrieval-Augmented Generation pipelines using modern frameworks, embedding models, and vector databases. ● Develop LLM-powered applications using prompt engineering, AI agents, LangGraph, and multi-agent workflows. ● Fine-tune, evaluate, deploy, and monitor machine-learning and deep-learning models. ● Build REST APIs and backend services for AI applications using FastAPI or similar frameworks. ● Design data-preprocessing, feature-engineering, model-training, and model-evaluation pipelines. ● Integrate structured and unstructured data sources to deliver accurate and context-aware AI solutions. ● Implement semantic search and document-retrieval architectures. ● Evaluate RAG and Generative AI solutions using appropriate quality and performance metrics. ● Collaborate with Data Engineering, DevOps, Product, and other cross-functional teams. ● Ensure the scalability, reliability, security, and performance of AI applications in production environments. ● Follow software-engineering best practices, coding standards, version-control processes, and Agile methodologies. ● Troubleshoot model, API, data-pipeline, and production-performance issues.
Requirements
Mandatory Skills
Programming and Backend Development ● Strong hands-on experience in Python. ● Strong working knowledge of SQL. ● Experience developing REST APIs using FastAPI or similar Python frameworks. ● Good understanding of object-oriented programming, modular development, testing, and software-engineering best practices. ● Experience working in Agile development environments. Machine Learning and Deep Learning Hands-on experience with: ● Scikit-learn ● TensorFlow ● PyTorch ● Keras Strong understanding of: ● Regression ● Classification ● Clustering ● Feature engineering ● Data preprocessing ● Model evaluation ● Hyperparameter tuning ● Model deployment and monitoring
NLP and Generative AI
● Minimum one year of hands-on experience working on GenAI or LLM-based projects. ● Strong understanding of Large Language Models and Natural Language Processing concepts. ● Experience in prompt engineering and prompt optimisation. ● Hands-on experience designing and implementing RAG architectures. ● Experience building agentic AI or multi-agent applications. ● Practical experience with: ○ LangChain ○ LangGraph ○ OpenAI APIs ○ Hugging Face ○ LangSmith
RAG and Vector Databases
● Experience working with vector databases and similarity-search technologies, including: ○ Pinecone ○ FAISS ● Knowledge of embedding models, chunking strategies, semantic search, document retrieval, and reranking. ● Experience evaluating RAG solutions using metrics or frameworks such as: ○ RAGAS ○ BLEU ○ ROUGE
AWS and DevOps
Hands-on experience with AWS services such as: ● Amazon EC2● Amazon S3 ● Amazon SageMaker ● Amazon Bedrock
Experience working with:
● Docker ● Git ● JIRA ● CI/CD pipelines
Preferred Qualifications
● Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline. ● Experience deploying AI and LLM applications in production environments. ● Understanding of LLM observability, hallucination control, guardrails, latency optimisation, and cost optimisation. ● Experience integrating enterprise data sources with GenAI applications. ● Strong analytical, problem-solving, communication, and stakeholder-management skills.
Candidate Eligibility
● Candidates must have 4–6 years of overall professional experience. ● At least one year of practical GenAI or LLM project experience is mandatory. ● Candidates must be immediate joiners. ● Candidates should be based in Noida, Gurugram, Delhi, or another NCR location. ● Candidates must be comfortable working in a hybrid model from the Gurugram office. ● Candidates should be available for an interview on August 1 or August 3, 2026.
Build and deploy enterprise AI systems from prototype to production, partnering with educational institutions and other customers on architecture, evaluation, integrations, reliability, and scaled adoption.
Build and deploy enterprise AI systems for healthcare and life sciences customers, combining hands-on engineering with technical leadership to deliver reliable production deployments, scaled adoption, and measurable outcomes.
Build AI agents, workflows, and integrations that transform how Sales, Marketing, Customer Success, Product, and Finance find, win, and grow customers, while establishing reliable shared data foundations.
Design, deploy, and maintain AI agents, machine learning models, and scalable LLM backend systems, integrating and optimizing production AI solutions with cross-functional teams.
Build and deliver production-grade GenAI solutions using modern LLMs and AI platforms, applying strong software engineering practices to solve business problems and create value for customers and colleagues.
