Brief Description Job Description: GenAI / AI/ML Engineer Experience: 2-4Years Location: Koramangala, Bangalore/ Technopark, Trivandrum Employment Type: Full-Time About the Role We are seeking a Python Developer with strong backend engineering expertise and hands-on exposure to Generative AI, Machine Learning, and Deep Learning to design, build, and scale AI-driven applications. The role involves developing production-grade AI solutions leveraging Large Language Models (LLMs), deep learning models, and cloud AI services across cloud or on-premises environments. You will be responsible for building high-performance backend services, integrating advanced AI/ML models, and enabling scalable API-driven platforms. The ideal candidate should have experience in building LLM-powered systems, implementing Agentic AI workflows, and applying AI-first approaches to solve business problems. You will work closely with cross-functional teams to deliver reliable, scalable, and secure AI solutions integrated into enterprise systems. Key Responsibilities • Design, develop, and integrate LLM-based solutions (e.g., OpenAI GPT, LLaMA, HuggingFace models) into enterprise products and workflows • Implement Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, chunking strategies, and fine-tuning for business use cases • Develop APIs and integration layers to seamlessly connect AI models with frontend and backend systems • Build and maintain scalable backend applications using Python with microservices architecture • Design and implement RESTful APIs using frameworks such as FastAPI (mandatory), Flask, or Django • Develop Agentic AI workflows including multi-agent coordination, tool/function calling, memory handling, and workflow orchestration • Integrate AI models into applications using APIs and ensure secure and efficient communication across systems • Collaborate effectively with frontend (Flutter) and backend (Node.js/Python) teams for smooth AI feature deployment • Test, debug, and manage API integrations using tools like cURL and other debugging mechanisms • Build and deploy AI services on cloud platforms using AWS services such as Lambda, S3, API Gateway, EC2, ECS/EKS, DynamoDB, and RDS • Leverage Amazon Bedrock and SageMaker for model deployment, orchestration, and scaling • Develop and integrate machine learning and deep learning models using frameworks such as TensorFlow, PyTorch, and scikit-learn • Work on NLP, classification, regression, clustering, anomaly detection, and time-series modeling problems • Build scalable data pipelines for data processing, training, validation, and inference • Ensure systems are secure, scalable, cost-optimized, and production-ready with proper monitoring and observability • Implement DevOps and MLOps best practices including CI/CD, model versioning, logging, and performance tracking • Collaborate with product teams and stakeholders to translate business requirements into AI-driven solutions • Contribute to architecture design, innovation, and continuous improvement of AI platforms Required Technical Skills: LLM & AI Integration (Mandatory – Hands-on) • Strong hands-on experience working with LLMs and Generative AI systems • Experience integrating LLMs such as OpenAI GPT, LLaMA, HuggingFace models into real-world applications • Experience with frameworks such as LangChain, LlamaIndex, LangGraph, ADK, or similar • Hands-on experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or OpenSearch • Proven ability to build and deploy RAG pipelines, embeddings-based retrieval systems, and prompt engineering workflows • Experience integrating AI models via APIs into live production systems Programming & Frameworks • Strong proficiency in Python for backend development, data processing, and AI/ML integration • Experience with FastAPI (mandatory), Flask, or Django for API development • Basic to intermediate understanding of Node.js for backend integration and collaboration • Basic understanding of Flutter to support frontend integration of AI APIs • Familiarity with cURL for testing, debugging, and managing API requests and responses Machine Learning & Deep Learning • Solid understanding of machine learning and deep learning concepts • Hands-on experience with frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn • Experience in NLP, neural networks, and modern AI architectures • Ability to train, validate, optimize, and deploy ML/DL models Data & Database Technologies • Experience with relational databases such as PostgreSQL or MySQL • Experience with NoSQL and vector databases such as MongoDB, Pinecone, or OpenSearch • Knowledge of data processing tools such as Pandas and NumPy • Familiarity with big data tools such as Spark or Hadoop (optional) Cloud & DevOps • Experience working with AWS cloud services including Lambda, S3, API Gateway, EC2, ECS/EKS, DynamoDB, and RDS • Knowledge of Amazon Bedrock and SageMaker is preferred • Experience with Docker and Kubernetes for containerization and orchestration • Familiarity with CI/CD pipelines and DevOps practices • Understanding of IAM, VPC, encryption, and secure system design Professional and Technical Skills • Strong understanding of microservices architecture and distributed systems • Expertise in API design, software architecture, and scalable system design • Strong problem-solving, analytical thinking, and debugging skills • Ability to design, build, test, deploy, and operate AI-powered systems end-to-end • Experience in performance optimization, scalability, latency, and cost trade-offs • Good communication skills with the ability to explain complex technical concepts to cross-functional teams • Ability to assess existing processes, identify improvement areas, and suggest AI-driven solutions • Awareness of latest technologies and industry trends Good to Have • Experience with advanced Agentic AI systems and workflow automation • Knowledge of Graph RAG and knowledge graph-based retrieval systems • Experience in prompt optimization, LLM fine-tuning, and model evaluation • Experience deploying AI/ML/GenAI solutions into production environments • Exposure to multiple cloud platforms such as AWS, Azure, or GCP • Familiarity with financial or enterprise domain systems • Experience with distributed systems, Snowflake, or large-scale data platforms Summary This role requires a strong foundation in Python backend development combined with hands-on experience in Generative AI, Machine Learning, and Deep Learning. The candidate should be capable of building scalable, production-ready AI systems, integrating advanced models, and enabling intelligent automation across enterprise workflows.