16 Vectordb Jobs

About The Opportunity : A fast-scaling technology company operating in the Enterprise AI / Generative AI sector, building production-grade LLM-driven products and intelligent automation for global clients. We deliver secure, low-latency generative systems that power conversational AI, summarization, code generation, and retrieval-augmented applications across cloud-native environments. We are hiring a Senior Generative AI Engineer (7+ years) to own architecture, model development, and production deployment of advanced generative systems. This is a fully remote role for candidates based in India. Role & Responsibilities : - Lead end-to-end design and delivery of Generative AI/LLM solutionsdata ingestion, pre-processing, model training/fine-tuning, evaluation, and scalable inference. - Develop and productionize transformer-based models (instruction-tuning, LoRA, quantization) using PyTorch/TensorFlow and Hugging Face tooling. - Architect and implement RAG pipelines integrating vector databases (FAISS/Milvus/Chroma), dense / sparse retrieval, and scalable embedding workflows. - Optimize inference throughput and latency using ONNX/TorchScript/TensorRT, autoscaling, and cost-efficient deployment patterns on cloud infra. - Define MLOps best practices : CI/CD for models, containerization, observability, automated retraining, drift detection and rollout strategies. - Mentor engineers, conduct code reviews, and collaborate with product & data science to translate research into reliable production systems. Skills & Qualifications : Must-Have : - 7+ years software/ML engineering experience with significant time on generative/LLM projects. - Strong proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable). - Hands-on experience with Hugging Face Transformers, tokenizers, training and fine-tuning workflows. - Proven experience building RAG systems and working with vector stores (FAISS, Milvus, Chroma) and embedding pipelines. - Experience deploying models to production using Docker, Kubernetes, and cloud services (AWS/GCP/Azure). - Solid software engineering practices : unit testing, CI/CD, code reviews, and monitoring for ML systems. Preferred : - Experience with model compression/acceleration (quantization, distillation), ONNX, or TensorRT. - Familiarity with LangChain or similar orchestration frameworks, agentic workflows, and tool-calling patterns. - Background in prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF) exposure. - Knowledge of data privacy, secure model serving, and compliance controls for enterprise deployments. Benefits & Culture Highlights : - Fully remote, India-based role with flexible hours and a results-oriented culture. - Opportunity to shape product architecture and scale cutting-edge generative AI for enterprise customers. - Collaborative environment with senior ML engineers, data scientists, and product stakeholdersmentorship and career growth. To apply, you should be passionate about bringing advanced generative models into production, comfortable with both research-to-production translation and the operational discipline required to run mission-critical AI systems.

About The Opportunity : A fast-scaling technology company operating in the Enterprise AI / Generative AI sector, building production-grade LLM-driven products and intelligent automation for global clients. We deliver secure, low-latency generative systems that power conversational AI, summarization, code generation, and retrieval-augmented applications across cloud-native environments. We are hiring a Senior Generative AI Engineer (7+ years) to own architecture, model development, and production deployment of advanced generative systems. This is a fully remote role for candidates based in India. Role & Responsibilities : - Lead end-to-end design and delivery of Generative AI/LLM solutionsdata ingestion, pre-processing, model training/fine-tuning, evaluation, and scalable inference. - Develop and productionize transformer-based models (instruction-tuning, LoRA, quantization) using PyTorch/TensorFlow and Hugging Face tooling. - Architect and implement RAG pipelines integrating vector databases (FAISS/Milvus/Chroma), dense / sparse retrieval, and scalable embedding workflows. - Optimize inference throughput and latency using ONNX/TorchScript/TensorRT, autoscaling, and cost-efficient deployment patterns on cloud infra. - Define MLOps best practices : CI/CD for models, containerization, observability, automated retraining, drift detection and rollout strategies. - Mentor engineers, conduct code reviews, and collaborate with product & data science to translate research into reliable production systems. Skills & Qualifications : Must-Have : - 7+ years software/ML engineering experience with significant time on generative/LLM projects. - Strong proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable). - Hands-on experience with Hugging Face Transformers, tokenizers, training and fine-tuning workflows. - Proven experience building RAG systems and working with vector stores (FAISS, Milvus, Chroma) and embedding pipelines. - Experience deploying models to production using Docker, Kubernetes, and cloud services (AWS/GCP/Azure). - Solid software engineering practices : unit testing, CI/CD, code reviews, and monitoring for ML systems. Preferred : - Experience with model compression/acceleration (quantization, distillation), ONNX, or TensorRT. - Familiarity with LangChain or similar orchestration frameworks, agentic workflows, and tool-calling patterns. - Background in prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF) exposure. - Knowledge of data privacy, secure model serving, and compliance controls for enterprise deployments. Benefits & Culture Highlights : - Fully remote, India-based role with flexible hours and a results-oriented culture. - Opportunity to shape product architecture and scale cutting-edge generative AI for enterprise customers. - Collaborative environment with senior ML engineers, data scientists, and product stakeholdersmentorship and career growth. To apply, you should be passionate about bringing advanced generative models into production, comfortable with both research-to-production translation and the operational discipline required to run mission-critical AI systems.

Role & Responsibilities : - Lead end-to-end design and delivery of Generative AI/LLM solutionsdata ingestion, pre-processing, model training/fine-tuning, evaluation, and scalable inference. - Develop and productionize transformer-based models (instruction-tuning, LoRA, quantization) using PyTorch/TensorFlow and Hugging Face tooling. - Architect and implement RAG pipelines integrating vector databases (FAISS/Milvus/Chroma), dense / sparse retrieval, and scalable embedding workflows. - Optimize inference throughput and latency using ONNX/TorchScript/TensorRT, autoscaling, and cost-efficient deployment patterns on cloud infra. - Define MLOps best practices : CI/CD for models, containerization, observability, automated retraining, drift detection and rollout strategies. - Mentor engineers, conduct code reviews, and collaborate with product & data science to translate research into reliable production systems. Skills & Qualifications : Must-Have : - 7+ years software/ML engineering experience with significant time on generative/LLM projects. - Strong proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable). - Hands-on experience with Hugging Face Transformers, tokenizers, training and fine-tuning workflows. - Proven experience building RAG systems and working with vector stores (FAISS, Milvus, Chroma) and embedding pipelines. - Experience deploying models to production using Docker, Kubernetes, and cloud services (AWS/GCP/Azure). - Solid software engineering practices : unit testing, CI/CD, code reviews, and monitoring for ML systems. Preferred : - Experience with model compression/acceleration (quantization, distillation), ONNX, or TensorRT. - Familiarity with LangChain or similar orchestration frameworks, agentic workflows, and tool-calling patterns. - Background in prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF) exposure. - Knowledge of data privacy, secure model serving, and compliance controls for enterprise deployments. Benefits & Culture Highlights : - Fully remote, India-based role with flexible hours and a results-oriented culture. - Opportunity to shape product architecture and scale cutting-edge generative AI for enterprise customers. - Collaborative environment with senior ML engineers, data scientists, and product stakeholdersmentorship and career growth. To apply, you should be passionate about bringing advanced generative models into production, comfortable with both research-to-production translation and the operational discipline required to run mission-critical AI systems.

About The Opportunity : A fast-scaling technology company operating in the Enterprise AI / Generative AI sector, building production-grade LLM-driven products and intelligent automation for global clients. We deliver secure, low-latency generative systems that power conversational AI, summarization, code generation, and retrieval-augmented applications across cloud-native environments. We are hiring a Senior Generative AI Engineer (7+ years) to own architecture, model development, and production deployment of advanced generative systems. This is a fully remote role for candidates based in India. Role & Responsibilities : - Lead end-to-end design and delivery of Generative AI/LLM solutionsdata ingestion, pre-processing, model training/fine-tuning, evaluation, and scalable inference. - Develop and productionize transformer-based models (instruction-tuning, LoRA, quantization) using PyTorch/TensorFlow and Hugging Face tooling. - Architect and implement RAG pipelines integrating vector databases (FAISS/Milvus/Chroma), dense / sparse retrieval, and scalable embedding workflows. - Optimize inference throughput and latency using ONNX/TorchScript/TensorRT, autoscaling, and cost-efficient deployment patterns on cloud infra. - Define MLOps best practices : CI/CD for models, containerization, observability, automated retraining, drift detection and rollout strategies. - Mentor engineers, conduct code reviews, and collaborate with product & data science to translate research into reliable production systems. Skills & Qualifications : Must-Have : - 7+ years software/ML engineering experience with significant time on generative/LLM projects. - Strong proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable). - Hands-on experience with Hugging Face Transformers, tokenizers, training and fine-tuning workflows. - Proven experience building RAG systems and working with vector stores (FAISS, Milvus, Chroma) and embedding pipelines. - Experience deploying models to production using Docker, Kubernetes, and cloud services (AWS/GCP/Azure). - Solid software engineering practices : unit testing, CI/CD, code reviews, and monitoring for ML systems. Preferred : - Experience with model compression/acceleration (quantization, distillation), ONNX, or TensorRT. - Familiarity with LangChain or similar orchestration frameworks, agentic workflows, and tool-calling patterns. - Background in prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF) exposure. - Knowledge of data privacy, secure model serving, and compliance controls for enterprise deployments. Benefits & Culture Highlights : - Fully remote, India-based role with flexible hours and a results-oriented culture. - Opportunity to shape product architecture and scale cutting-edge generative AI for enterprise customers. - Collaborative environment with senior ML engineers, data scientists, and product stakeholdersmentorship and career growth.

About The Opportunity : A fast-scaling technology company operating in the Enterprise AI / Generative AI sector, building production-grade LLM-driven products and intelligent automation for global clients. We deliver secure, low-latency generative systems that power conversational AI, summarization, code generation, and retrieval-augmented applications across cloud-native environments. We are hiring a Senior Generative AI Engineer (7+ years) to own architecture, model development, and production deployment of advanced generative systems. This is a fully remote role for candidates based in India. Role & Responsibilities : - Lead end-to-end design and delivery of Generative AI/LLM solutionsdata ingestion, pre-processing, model training/fine-tuning, evaluation, and scalable inference. - Develop and productionize transformer-based models (instruction-tuning, LoRA, quantization) using PyTorch/TensorFlow and Hugging Face tooling. - Architect and implement RAG pipelines integrating vector databases (FAISS/Milvus/Chroma), dense / sparse retrieval, and scalable embedding workflows. - Optimize inference throughput and latency using ONNX/TorchScript/TensorRT, autoscaling, and cost-efficient deployment patterns on cloud infra. - Define MLOps best practices : CI/CD for models, containerization, observability, automated retraining, drift detection and rollout strategies. - Mentor engineers, conduct code reviews, and collaborate with product & data science to translate research into reliable production systems. Skills & Qualifications : Must-Have : - 7+ years software/ML engineering experience with significant time on generative/LLM projects. - Strong proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable). - Hands-on experience with Hugging Face Transformers, tokenizers, training and fine-tuning workflows. - Proven experience building RAG systems and working with vector stores (FAISS, Milvus, Chroma) and embedding pipelines. - Experience deploying models to production using Docker, Kubernetes, and cloud services (AWS/GCP/Azure). - Solid software engineering practices : unit testing, CI/CD, code reviews, and monitoring for ML systems. Preferred : - Experience with model compression/acceleration (quantization, distillation), ONNX, or TensorRT. - Familiarity with LangChain or similar orchestration frameworks, agentic workflows, and tool-calling patterns. - Background in prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF) exposure. - Knowledge of data privacy, secure model serving, and compliance controls for enterprise deployments. Benefits & Culture Highlights : - Fully remote, India-based role with flexible hours and a results-oriented culture. - Opportunity to shape product architecture and scale cutting-edge generative AI for enterprise customers. - Collaborative environment with senior ML engineers, data scientists, and product stakeholdersmentorship and career growth. To apply, you should be passionate about bringing advanced generative models into production, comfortable with both research-to-production translation and the operational discipline required to run mission-critical AI systems.

Primary Role Title : Senior LLM Engineer. About The Opportunity : We are a fast-growing enterprise AI & data science consultancy serving global clients across finance, healthcare, and enterprise software. The team builds production-grade LLM-driven productsRAG systems, intelligent assistants, and custom inference pipelinesthat deliver measurable business outcomes. Location : India (Hybrid). Role & Responsibilities : - Design, fine-tune and productionize large language models (instruction tuning, LoRA/PEFT) using PyTorch and Hugging Face tooling for real-world applications. - Architect and implement RAG pipelines : embeddings generation, chunking strategies, vector search integration (FAISS/Pinecone/Milvus) and relevance tuning for high-quality retrieval. - Build scalable inference services and APIs (FastAPI/Falcon), containerize (Docker) and deploy to cloud/Kubernetes with low-latency and cost-optimized inference (quantization, ONNX/Triton). - Collaborate with data engineers and ML scientists to productionize data pipelines, automate retraining, monitoring, evaluation and drift detection. - Drive prompt-engineering, evaluation frameworks and safety/guardrail implementation to ensure reliable, explainable LLM behavior in production. - Establish engineering best-practices (Git workflows, CI/CD, unit tests, observability) and mentor junior engineers to raise team delivery standards. Skills & Qualifications : Must-Have : - 4+ years in data science/ML engineering with demonstrable experience building and shipping LLM-based solutions to production. - Strong Python engineering background and hands-on experience with PyTorch and Hugging Face Transformers (fine-tuning, tokenizers, model optimization). - Practical experience implementing RAG : embeddings, vector DBs (FAISS/Pinecone/Weaviate/Milvus), chunking and retrieval tuning. - Production deployment experience : Docker, Kubernetes, cloud infra (AWS/GCP/Azure) and inference optimization (quantization, batching, ONNX/Triton). Preferred : - Experience with LangChain/LangGraph or similar orchestration frameworks, and building agentic workflows. - Familiarity with ML observability, model governance, safety/bias mitigation techniques and cost/performance trade-offs for production LLMs. Benefits & Culture Highlights : - Hybrid working model in India with flexible hours, focused on outcomes and work-life balance. - Opportunity to work on cutting-edge GenAI engagements for enterprise customers and accelerate your LLM engineering career. - Collaborative consultancy culture with mentorship, learning stipend and clear growth paths into technical leadership. This role is with Zorba Consulting India. If you are an experienced LLM practitioner who enjoys end-to-end ownershipfrom research experiments to robust production systemsapply with your resume and a short note on a recent LLM project you led (models, infra, and outcomes). Zorba Consulting India is an equal opportunity employer committed to diversity and inclusion.

Role & Responsibilities : - Design, fine-tune and productionize large language models (instruction tuning, LoRA/PEFT) using PyTorch and Hugging Face tooling for real-world applications. - Architect and implement RAG pipelines : embeddings generation, chunking strategies, vector search integration (FAISS/Pinecone/Milvus) and relevance tuning for high-quality retrieval. - Build scalable inference services and APIs (FastAPI/Falcon), containerize (Docker) and deploy to cloud/Kubernetes with low-latency and cost-optimized inference (quantization, ONNX/Triton). - Collaborate with data engineers and ML scientists to productionize data pipelines, automate retraining, monitoring, evaluation and drift detection. - Drive prompt-engineering, evaluation frameworks and safety/guardrail implementation to ensure reliable, explainable LLM behavior in production. - Establish engineering best-practices (Git workflows, CI/CD, unit tests, observability) and mentor junior engineers to raise team delivery standards. Skills & Qualifications : Must-Have : - 4+ years in data science/ML engineering with demonstrable experience building and shipping LLM-based solutions to production. - Strong Python engineering background and hands-on experience with PyTorch and Hugging Face Transformers (fine-tuning, tokenizers, model optimization). - Practical experience implementing RAG : embeddings, vector DBs (FAISS/Pinecone/Weaviate/Milvus), chunking and retrieval tuning. - Production deployment experience : Docker, Kubernetes, cloud infra (AWS/GCP/Azure) and inference optimization (quantization, batching, ONNX/Triton). Preferred : - Experience with LangChain/LangGraph or similar orchestration frameworks, and building agentic workflows. - Familiarity with ML observability, model governance, safety/bias mitigation techniques and cost/performance trade-offs for production LLMs. Benefits & Culture Highlights : - Hybrid working model in India with flexible hours, focused on outcomes and work-life balance. - Opportunity to work on cutting-edge GenAI engagements for enterprise customers and accelerate your LLM engineering career. - Collaborative consultancy culture with mentorship, learning stipend and clear growth paths into technical leadership. This role is with Zorba Consulting India. If you are an experienced LLM practitioner who enjoys end-to-end ownershipfrom research experiments to robust production systemsapply with your resume and a short note on a recent LLM project you led (models, infra, and outcomes). Zorba Consulting India is an equal opportunity employer committed to diversity and inclusion.

Oracle Cerner in Bangalore is seeking a Software Developer 5 with over 10 years of experience. The role requires a skilled hands-on architect proficient in Python, with expertise in Java, Agentic AI, LangGraph, Vector DBs, OpenSearch, and LLM-based systems. The ideal candidate excels in system design, mentors senior engineers, directs technical aspects, and ensures the delivery of scalable, secure, and high-performing AI services. Ready to shape the future of healthcare AI? Apply now and be a part of building the clinical agentic infrastructure for tomorrow. The OHAI Agent Engineering Team is pioneering the next generation of intelligent agent frameworks, delivering transformative solutions to elevate healthcare services and drive exceptional customer experiences. Our cutting-edge platform seamlessly integrates advanced automation, clinical intelligence, and user-centric designempowering healthcare providers to deliver proactive, personalized care and setting a new standard for operational excellence and patient delight. Join us as we shape the future of healthcare with innovation, passion, and impact. We are seeking a Consultant Member of Technical Staff with deep expertise in healthcare technologies, Agentic AI frameworks, and modern data/AI infrastructure to join our Clinical AI team. This role is pivotal in shaping our next-generation Clinical Agentic AI Platform, enabling dynamic, context-aware care pathways for healthcare providers and patients. Key Responsibilities: Architect and lead the development of clinical agent-based AI systems using LangGraph or similar frameworks. Collaborate with product and clinical informatics teams to design AI-driven care pathways and decision support systems. Define and evolve the technical roadmap, aligning with compliance, performance, and integration standards. Lead the implementation of LangGraph-based agents, integrating them with Vector Databases, OpenSearch, and other retrieval-augmented generation (RAG) pipelines. Design and guide data pipelines for LLM-based applications, ensuring real-time contextual understanding. Mentor and coach senior and mid-level engineers; foster a culture of technical excellence and innovation. Conduct design reviews, enforce code quality standards, and ensure scalable, maintainable solutions. Collaborate with platform teams on observability, deployment automation, and runtime performance optimization. Stay current with evolving AI trends, particularly in the LLMOps / Agentic AI space, and evaluate emerging tools and frameworks.

At Skillsoft, we propel organizations and people to grow together through transformative learning experiences. We believe every team member has the potential to be AMAZING. Join us in our quest to transform learning and help individuals unleash their edge. Are you ready to shape the future of learning through cutting-edge AI As a Principal AI/Machine Learning Engineer at Skillsoft, youll dive into the heart of innovation, crafting intelligent systems that empower millions worldwide. From designing generative AI solutions to pioneering agentic workflows, youll collaborate with internal and external teams to transform knowledge into a catalyst for growthunleashing your edge while helping others do the same. Join us in redefining eLearning for the worlds leading organizations! Responsibilities Hands-on Principal AI/ML engineer, driving technical innovation Partner with product owners to define visionary AI features Collaborate cross-functionally to assess impacts of new AI capabilities Consult and guide teams to productize prototypes with provable accuracy Lead research and selection of COTS and development of in-house AI/ML technologies Evaluate foundational models and emerging AI advancements Explore new technologies and design patterns through impactful prototypes Present research and insights to inspire innovation across teams Guide, design and testing of agentic workflows and prompt engineering Fine-tune models, validate efficacy with metrics, and ensure reliability Evaluate and guide synthetic data generation for training and validation Design and guide scalable data pipelines for AI/ML training and inference Oversee data analysis, curation, and preprocessing Collaborate with external partners on AI development and integration Establish AI design best practices and standards for alignment Contribute to patentable AI innovations Utilize and apply generative AI to increase productivity for yourself and the organization Environment, Tools & Technologies Agile/Scrum Operating Systems Mac, Linux JavaScript, Node.js, Python PyTorch, Tensorflow, Keras, OpenAI, Anthropic, and friends Langchain, Langgraph, etc. APIs GraphQL, REST Docker, Kubernetes Amazon Web Services (AWS), MS Azure Sagemaker, NIMS SQL: Postgres RDS NoSQL: Cassandra, Elasticsearch (VectorDb) Messaging Kafka, RabbitMQ, SQS Monitoring Prometheus, ELK GitHub, IDE (your choice) Skills & Qualifications 8+ Years of Relevant Industry Experience (with a Masters Degree Preferred) Experience with LLMs and fine-tuning foundation models Development experience including unit testing Design and documentation experience of new APIs, data models, service interactions Familiarity with and ability to explain: Agentic AI development and testing AI security and data privacy concerns Synthetic data generation and concerns Foundation model fine-tuning Generative AI prompt engineering and challenges Attributes For Success Proactive, Independent, Adaptable Collaborative team player Customer service minded with an ownership mindset Excellent analytic and communication skills Ability and desire to coach and mentor other developers Passionate, curious, open to new ideas, and ability to research and learn new technologies More About Skillsoft Skillsoft delivers online learning, training, and talent solutions to help organizations unleash their edge . Leveraging immersive, engaging content, Skillsoft enables organizations to unlock the potential in their best assets their people and build teams with the skills they need for success. Empowering 36 million learners and counting, Skillsoft democratizes learning through an intelligent learning experience and a customized, learner-centric approach to skills development with resources for Leadership Development, Business Skills, Technology & Development, Digital Transformation, and Compliance. Skillsoft is partner to thousands of leading global organizations, including many Fortune 500 companies. The company features three award-winning systems that support learning, performance and success: Skillsoft learning content, the Percipio intelligent learning experience platform, which offers measurable impact across the entire employee lifecycle. Learn more at www.skillsoft.com. Thank you for taking the time to learn more about us. If this opportunity intrigues you, we would love for you to apply! NOTE TO EMPLOYMENT AGENCIES: We value the partnerships we have built with our preferred vendors. Skillsoft does not accept unsolicited resumes from employment agencies. All resumes submitted by employment agencies directly to any Skillsoft employee or hiring manager in any form without a signed Skillsoft Employment Agency Agreement on file and search engagement for that position will be deemed unsolicited in nature. No fee will be paid in the event the candidate is subsequently hired as a result of the referral or through other means. Skillsoft is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information, and other legally protected categories. Show more Show less

Are you a graduating student from the class of 2025/26 seeking an internship opportunity Do you possess a keen interest in engineering and AgenticAI, aspiring to build your career in GenAI If so, we present you with an exciting chance to explore and grow. Your qualifications and essential skills should include a B.Tech degree in Computer Science, Mathematics, Engineering, or a related field by 2025/26. Proficiency in Python is a must-have skill. Additionally, familiarity or experience with AI frameworks such as Tensorflow, Pytorch, RAG, CRAG, GraphRAG, HuggingFace, LangChain, LangGraph, VectorDB, MCP, and AWS is highly desirable. The ability to commit to a full-time internship, work independently with minimal supervision, demonstrate a passion for excellence, showcase creative thinking, possess commercial awareness, and maintain a focus on achieving set goals are all important attributes. As an intern, you can look forward to a range of perks and benefits, including the potential opportunity for a job offer based on your performance. You will have the chance to collaborate with experienced entrepreneurs, immerse yourself in cutting-edge research and technology, and contribute to an exciting and rapidly expanding field. Remuneration may also be provided based on your performance. This internship opportunity is full-time and spans a duration of 2-3 months. The work setting is hybrid, offering a mix of in-person and remote work experiences.,

Role & responsibilities: Design and lead technical architecture for secure, multi-tenant systems. Architect resilient microservices using Node.js, Python, and Azure. Integrate OpenAI LLMs and Kore.ai conversational AI workflows for intelligent experiences. Guide prompt engineering strategy and LLM fine-tuning aligned with product goals. Drive implementation of high-throughput messaging and data systems using Redis, RabbitMQ, Clickhouse, VectorDB, and MongoDB. Manage configuration and performance tuning of APISIX (API Gateway) and Nginx (Reverse Proxy). Lead design for context-aware session management and semantic relevance frameworks. Define secure architectural patterns with RBAC, token lifecycle, and deep observability. Collaborate with and mentor backend, frontend, and DevOps teams to ensure system alignment. Establish and maintain architectural documentation and technical standards. Preferred candidate profile: Deep experience in cloud-native architecture and microservices design. Hands-on skills with Node.js, Python, React, and Azure. Proven success in LLM integration with tools like OpenAI and Kore.ai. Strong grasp of messaging, caching, and high-performance data pipelines. Familiarity with APISIX, reverse proxies, and distributed systems security. Experience with vector databases, time-series storage, and semantic search.

As a Generative AI Specialist, you will be responsible for developing GenAI LLM model-driven solutions using state-of-the-art models such as OpenAI, Gemini, and Claude, as well as open-source models like Llama and Mistral. Your main role will involve fine-tuning and training models, with a focus on implementing projects involving Agents, Tools, and RAG solutions. You should have hands-on experience in integrating LLMs with VectorDBs like Chromadb, Faiss, and Pinecone. To excel in this role, you must demonstrate expertise in PEFT, quantization of models, and have experience working with tools such as Tensorflow, Pytorch, Python, Hugging Face, and Transformers. Proficiency in data preparation, analysis, and deep learning model development is highly preferred. Additionally, familiarity with deploying models in AWS is desired but not mandatory. Key skills for this role include OpenAI, Gemini, LangChain, Transformers, Hugging Face, Python, Pytorch, Tensorflow, VectorDBs (Chromadb, Faiss, Pinecone). You should have a track record of at least 1-2 live implementations of Generative AI-driven solutions, with extensive experience in deploying chatbots, knowledge search, and NLP solutions. A solid background in implementing machine learning and deep learning solutions for a minimum of 2 years is also expected. This position is based in Chennai, with the work shift from 11 AM to 8 PM. The mode of work is from the office, and the office address is 4th Floor, Techno Park, 10, Rajiv Gandhi Salai, Customs Colony, Sakthi Nagar, Thoraipakkam, Chennai 600097.,

You have a total of 8+ years of experience, with at least 4 years in AI, ML, and Gen AI technologies. You have successfully led and expanded AI/ML teams and projects. Your expertise includes a deep understanding and practical experience in AI, ML, Deep Learning, and Generative AI concepts. You are proficient in ML frameworks like PyTorch and/or TensorFlow and have worked with ONNX runtime, model optimization, and hyperparameter tuning. You possess solid experience in DevOps, SDLC, CI/CD, and MLOps practices, with a tech stack that includes Docker, Kubernetes, Jenkins, Git, CI/CD, RabbitMQ, Kafka, Spark, Terraform, Ansible, Prometheus, Grafana, and ELK stack. You have deployed AI models at an enterprise scale and are skilled in data preprocessing, feature engineering, and handling large-scale data. Your expertise extends to image and video processing, object detection, image segmentation, and other computer vision tasks. In addition, you have proficiency in text analysis, sentiment analysis, language modeling, and various NLP applications. You also have experience in speech recognition, audio classification, and signal processing techniques. Your knowledge includes RAG, VectorDB, GraphDB, and Knowledge Graphs. You have extensive experience working with major cloud platforms such as AWS, Azure, and GCP for AI/ML deployments, and integrating cloud-based AI services and tools like AWS SageMaker, Azure ML, and Google Cloud AI. As for soft skills, you exhibit strong leadership and team management abilities, excellent verbal and written communication skills, strategic thinking, problem-solving capabilities, adaptability to the evolving AI/ML landscape, collaboration skills, and the capacity to translate market requirements into technological solutions. Moreover, you have a deep understanding of industry dynamics and a demonstrated ability to foster innovation and creative problem-solving within a team.,

Job description We are seeking a highly skilled GenAI Solution Architect to join our growing team. In this role, you will leverage your expertise in Generative AI, machine learning, and natural language processing (NLP) to design and implement innovative AI-driven solutions. The ideal candidate will have a deep understanding of architectural design, data strategies, AI agents, and the latest advancements in language models. You will play a key role in delivering cutting-edge solutions, working with large-scale data, and building systems that enhance automation, intelligence, and efficiency for our clients. Key Responsibilities GenAI Solutioning & Architectural Design Lead the design and implementation of end-to-end Generative AI solutions, ensuring scalable, robust, and efficient architecture that aligns with business needs. Data Strategy & Management Develop and execute strategies for data collection, cleaning, transformation, and integration for AI model development. Apply best practices for data pipeline design and optimization. AI Agents Development Design and implement intelligent AI agents using advanced techniques in NLP and machine learning to improve automation, user interaction, and decision-making processes.Fine-tuning & Prompt Engineering Fine-tune pre-trained models (e.g., GPT, BERT, etc.) and optimize prompt engineering techniques to drive high-quality, actionable outputs for diverse business use cases. Machine Learning & Deep Learning Models Build, train, and deploy machine learning models, including deep learning models, for complex AI applications across various domains. LLM Provisioning from CSPs Lead the provisioning and customization of Large Language Models (LLMs) from major Cloud Service Providers (CSPs) such as Azure, AWS, and Google Cloud, ensuring optimal performance and cost-effectiveness. Technologies & Frameworks Utilize Langchain, Crew AI, and VectorDB for building, integrating, and scaling NLP solutions, and leverage Flask/FastAPI for model deployment and integration. Database & SQL Management Work with databases (SQL/NoSQL) for data storage, querying, and management to support AI model development and deployment.Tokenization & NLP Techniques Apply advanced tokenization techniques to preprocess and analyze data for NLP tasks, enhancing model efficiency and performance. Deployment & Evaluation Oversee the deployment of AI models, ensuring smooth integration with production systems, and perform rigorous evaluation of LLMs for accuracy, efficiency, and scalability. Required Skills & Qualifications Proven experience in GenAI solutioning and architectural design for large-scale AI systems. Expertise in data cleaning, transformation, and data strategy to drive AI and machine learning initiatives. Strong hands-on experience with AI agents, prompt engineering, and fine-tuning LLMs for business applications. Proficiency in machine learning models, deep learning techniques, and NLP applications. Deep knowledge of LLM provisioning from different Cloud Service Providers (CSPs) (e.g., AWS, Azure, Google Cloud). Experience with Langchain, CrewAI, VectorDB, Flask, FastAPI, and related frameworks for model integration and deployment.Strong database skills, with proficiency in SQL and experience in working with NoSQL databases. Familiarity with advanced tokenization techniques and their applications in NLP. Experience with model deployment, integration, and LLM evaluation for real-world applications.

I’m building an AI-powered internal knowledge assistant that helps teams find answers instantly from Notion, Drive, Slack, GitHub, and more. If you're excited about LLMs, RAG pipelines, LangChain, and building fast from 0 1, let’s talk.

Tech stack required: Programming languages: Python Public Cloud: AzureFrameworks: Vector Databases such as Milvus, Qdrant/ ChromaDB, or usage of CosmosDB or MongoDB as Vector stores. Knowledge of AI Orchestration, AI evaluation and Observability Tools. Knowledge of Guardrails strategy for LLM. Knowledge on Arize or any other ML/LLM observability tool. Experience: Experience in building functional platforms using ML, CV, LLM platforms. Experience in evaluating and monitoring AI platforms in production Nice to have requirements to the candidate Excellent communication skills, both written and verbal. Strong problem-solving and critical-thinking abilities. Effective leadership and mentoring skills. Ability to collaborate with cross-functional teams and stakeholders. Strong attention to detail and a commitment to delivering high-quality solutions. Adaptability and willingness to learn new technologies. Time management and organizational skills to handle multiple projects and priorities.