466 Rag Jobs - Page 7

Job Position Title: Senior Associate_ APA Developer_Agentic Automation_Advisory_Bangalore Responsibilities: Design and develop agentic automation workflows using frameworks such as LangGraph, AutoGen, CrewAI, and other multi-agent systems (e.g., MCP, A2A) to automate complex business processes. Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced contextual understanding and accurate response generation in automation tasks. Integrate open-source LLMs (e.g. LLaMA) and closed-source LLMs (e.g., OpenAI, Gemini, Vertex AI) to power agentic systems and generative AI applications. Develop robust Python-based solutions using libraries like LangChain, Transformers, Pandas, and PyTorch for automation and AI model development. Implement and manage CI/CD pipelines, Git workflows, and software development best practices to ensure seamless deployment of automation solutions. Work with structured and unstructured data, applying prompt engineering and fine-tuning techniques to enhance LLM performance for specific use cases. Query and manage databases (e.g., SQL, NoSQL) for data extraction, transformation, and integration into automation workflows. Collaborate with stakeholders to translate technical solutions into business value, delivering clear presentations and documentation. Stay updated on advancements in agentic automation, generative AI, and LLM technologies to drive innovation and maintain competitive edge. Ensure scalability, security, and performance of deployed automation solutions in production environments. Experience: 4+ years of hands-on experience in AI/ML, generative AI, or automation development. Proven expertise in agentic frameworks like LangGraph, AutoGen, CrewAI, and multi-agent systems. Experience building and deploying RAG-based solutions for automation or knowledge-intensive applications. Hands-on experience with open-source LLMs (Hugging Face) and closed-source LLMs (OpenAI, Gemini, Vertex AI). Technical Skills: Advanced proficiency in Python and relevant libraries (LangChain, Transformers, Pandas, PyTorch, Scikit-learn). Strong SQL skills for querying and managing databases (e.g., PostgreSQL, MongoDB). Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions), Git workflows, and containerization (e.g., Docker, Kubernetes). Experience with Linux (Ubuntu) and cloud platforms (AWS, Azure, Google Cloud) for deploying automation solutions. Knowledge of automation tools (e.g., UiPath, Automation Anywhere) and workflow orchestration platforms. Soft Skills: Exceptional communication skills to articulate technical concepts to non-technical stakeholders. Strong problem-solving and analytical skills to address complex automation challenges. Ability to work collaboratively in a fast-paced, client-facing environment. Proactive mindset with a passion for adopting emerging technologies. Preferred Qualifications Experience with multi-agent coordination protocols (MCP) and agent-to-agent (A2A) communication systems. Familiarity with advanced generative AI techniques, such as prompt chaining, tool-augmented LLMs, and model distillation. Exposure to enterprise-grade automation platforms or intelligent process automation (IPA) solutions. Contributions to open-source AI/automation projects or publications in relevant domains. Certification in AI, cloud platforms, or automation technologies (e.g., AWS Certified AI Practitioner, RPA Developer). Mandatory skill sets: Agentic, LLM, RAG, AIML, LangGchain Preferred skill sets: Agentic, LLM, RAG, AIML, LangGchain, Gen AI Years of experience required: 4-7 Years

Role: We are seeking an experienced and innovative Senior Full Stack Developer with at least 5 years of expertise in Python and front-end frameworks such as React. The ideal candidate will possess deep knowledge of AI integration, agent-based system development, and a passion for delivering sophisticated, scalable applications. You will play a crucial role in designing, developing, and maintaining our cutting-edge agentic AI platform. Responsibilities: Your Major Job responsibilities, but not limited to, shall be as under: Design, develop, and maintain scalable and robust full-stack applications using Python (backend) and React (frontend) . Architect and build intelligent AI-driven agents , integrating advanced AI capabilities such as natural language processing , retrieval-augmented generation (RAG) , and machine learning models . Collaborate closely with cross-functional teams including product managers, data scientists, and UX designers to implement comprehensive product solutions. Ensure the responsiveness, reliability, and security of web applications deployed across cloud environments. Lead and mentor junior developers , conducting code reviews and ensuring adherence to best practices in software engineering. Qualifications & Requirements: Minimum of 5 years of experience as a Full Stack Developer. Expert-level proficiency in Python and hands-on experience with frameworks such as Django, Flask, or FastAPI. Strong front-end development skills, particularly with React and related technologies (Redux, Hooks, Context API). Demonstrated expertise in AI technologies, including natural language processing, embeddings, retrieval-augmented generation (RAG), and large language models (LLMs). Experience designing and implementing autonomous AI agents or similar intelligent systems. Familiarity with databases (PostgreSQL, MongoDB, vector databases), cloud platforms (AWS, Azure, Google Cloud), and containerization technologies (Docker, Kubernetes). Exceptional problem-solving abilities, communication skills, and a proven track record of delivering high-quality software products. Preferred Qualification: Prior experience in developing enterprise-grade AI solutions. Familiarity with agentic frameworks and protocols. Contributions to open-source AI or web projects.

As an AI Software Engineer at DHL IT Services, you will be part of a global team of over 5600 IT professionals dedicated to connecting people and driving the global economy through continuous innovation and sustainable digital solutions. Your role will involve shaping the technology backbone of the world's largest logistics company, pushing boundaries across all dimensions of logistics. At DHL IT Services, we prioritize digitalization and are committed to providing exceptional employee experiences as reflected in our #GreatPlaceToWork certification. You will play a crucial role as an AI Engineer, serving as a pathfinder for the Engineering team. Your responsibilities will include understanding on-ground challenges and devising solutions to enhance efficiency in delivering solutions for faster time-to-market. Proficiency in leveraging AI tools for real-world use cases and improving productivity will be essential. To excel in this role, you must have experience in Python, Prompt Engineering, Generative AI models, and AI use cases application. Knowledge of AI workflow tools like LangChain and n8n will be advantageous in enhancing our business and IT processes for better efficiency. Your ability to break down tasks to use the appropriate learning models and ensure high-quality results through context engineering using RAG and MCP protocols is crucial. Working independently and effectively prioritizing and organizing tasks under time and workload pressure are key skills required for this role. You can expect to collaborate with multinational teams across the globe, making proficiency in spoken and written English highly valuable. In addition to a challenging and rewarding work environment, we offer a range of benefits including hybrid work arrangements, generous annual leave, comprehensive medical insurance coverage for you, your spouse, and children, as well as opportunities for in-house training programs and professional certifications. Join us on this exciting journey to drive innovation and digital transformation in the logistics industry. #DHL #DHLITServices #GreatPlace,

What will you do Voice AI Stack Ownership: Build and own the end-to-end voice bot pipeline ASR, NLU, dialog state management, tool calling, and TTS to create a natural, human-like conversation experience. LLM Orchestration & Tooling: Architect systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM. RAG Integration: Implement retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs. Vector Store & Memory: Design scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding. Latency Optimization: Engineer low-latency, streaming ASR + TTS pipelines and fine-tune turn-taking models for natural conversation. Model Tuning & Hallucination Control: Use fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals. Instrumentation & QA Looping: Build robust observability, run real-time call QA pipelines, and analyze interruptions, hallucinations, and fallbacks. Cross-functional Collaboration: Work closely with product, infra, and leadership to scale this bot to thousands of US dealerships. What will make you successful in this role Architect-level thinking: You understand how ASR, LLMs, memory, and tools fit together and can design modular, observable, and resilient systems. LLM Tooling Mastery: You've implemented tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows. Fluency in Vector Search & RAG: You know how to chunk, embed, index, and retrieve and how to avoid prompt bloat and token overflow. Latency-First Mindset: You debug token delays, know the cost of each API hop, and can optimize round-trip time to keep calls human-like. Grounding > Hallucination: You know how to trace hallucinations back to weak prompts, missing guardrails, or lack of tool access and fix them. Prototyper at heart: You're not scared of building from scratch and iterating fast, using open-source or hosted tools as needed. What you must have 5+ years in AI/ML or voice/NLP systems with real-time experience Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models Solid understanding of latency optimization, streaming inference, and real-time audio pipelines Hands-on with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP) Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior

You are an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role. Your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Proficiency in Python is a must, along with hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially while working with large datasets. You have experience deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. Your responsibilities as a Lead Data Scientist include guiding and mentoring a high-performance team on the latest technology landscape, patterns, and design standards. You provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems. Your role involves developing and deploying machine learning/deep learning models to address key business challenges, applying various techniques in statistical modeling, data preprocessing, feature engineering, and more. You are proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems. Furthermore, you design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems. Your qualifications include a Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Your primary skills encompass Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms. Your secondary skills involve expertise in designing scalable and efficient model architectures, the ability to assess and forecast financial requirements of data science projects, and strong communication skills for conveying technical concepts to stakeholders. As a Lead Data Scientist, you stay updated with the latest advancements in data science and machine learning, particularly in generative AI, to evaluate their potential applications and serve as a primary point of contact for client managers.,

As a Senior AI Engineer - Voice AI / Autonomous Agents at Spyne, you will have the opportunity to own and build Spynes in-house voice bot stack. In this high-impact individual contributor role, you will be at the intersection of LLMs, ASR/TTS, and voice UX, focusing on creating deeply human, latency-optimized conversations between auto dealerships and their customers. Your main responsibilities will include: Voice AI Stack Ownership: Building and owning the end-to-end voice bot pipeline, including ASR, NLU, dialog state management, tool calling, and TTS to deliver a natural, human-like conversation experience. LLM Orchestration & Tooling: Architecting systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM. RAG Integration: Implementing retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs. Vector Store & Memory: Designing scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding. Latency Optimization: Engineering low-latency, streaming ASR + TTS pipelines and fine-tuning turn-taking models for natural conversation. Model Tuning & Hallucination Control: Using fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals. Instrumentation & QA Looping: Building robust observability, running real-time call QA pipelines, and analyzing interruptions, hallucinations, and fallbacks. Cross-functional Collaboration: Working closely with product, infra, and leadership to scale this bot to thousands of US dealerships. To be successful in this role, you should possess: Architect-level thinking: Understanding how ASR, LLMs, memory, and tools fit together and having the ability to design modular, observable, and resilient systems. LLM Tooling Mastery: Implementing tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows. Fluency in Vector Search & RAG: Knowing how to chunk, embed, index, and retrieve, while avoiding prompt bloat and token overflow. Latency-First Mindset: Debugging token delays, understanding the cost of each API hop, and optimizing round-trip time to maintain human-like interactions. Grounding > Hallucination: Tracing hallucinations back to weak prompts, missing guardrails, or lack of tool access and effectively addressing them. Prototyper at heart: Being unafraid of building from scratch and iterating quickly, utilizing open-source or hosted tools as necessary. The ideal candidate will have: 5+ years of experience in AI/ML or voice/NLP systems with real-time experience. Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering. Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools. Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models. Solid understanding of latency optimization, streaming inference, and real-time audio pipelines. Hands-on experience with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP). Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior. Working at Spyne offers real-world AI impact at scale, a high-performing team that balances speed with technical depth, high autonomy and visibility from day one, rapid career acceleration, access to MacBook and all necessary tools and compute, a flat structure with real work focus, and no BS. Join us in redefining how cars are marketed and sold with cutting-edge Generative AI.,

As a Full-Stack AI App Developer at EMO Energy, you will play a key role in reimagining urban mobility, energy, and fleet operations through our AI-driven super app. You will have the opportunity to take full ownership of building and deploying a cutting-edge energy infrastructure startup in India. Your responsibilities will include architecting and developing a full-stack AI-enabled application, designing modular frontend views using React.js or React Native, creating intelligent agent interfaces, building secure backend APIs for managing energy and fleet operations, integrating real-time data workflows, implementing fleet tracking dashboards, and optimizing performance across various platforms. Collaboration with the founding team, ops team, and hardware teams will be essential to iterate fast and solve real-world logistics problems. The ideal candidate for this role should have a strong command of front-end frameworks such as React.js, experience with back-end technologies like FastAPI, Node.js, or Django, proficiency in TypeScript or Python, familiarity with GCP services, Docker, GitHub Actions, and experience with mobile integrations and AI APIs. End-to-end ownership of previous applications, strong UI/UX product sensibility, and experience in building dashboards or internal tools will be valuable assets. Additionally, the ability to adapt to ambiguity, communicate technical decisions to non-engineers, and a passion for clean code and impactful work are crucial for success in this role. If you are a highly motivated individual with a passion for AI-driven applications and a desire to lead the development of a cutting-edge fleet/energy platform, then this role at EMO Energy is the perfect opportunity for you. Join us in revolutionizing the future of urban mobility and energy infrastructure in India.,

As an AI Developer, you will be responsible for designing and developing AI/ML models focused on natural language understanding, intelligent automation, and real-time decision-making utilizing NLP, LLMs, and RAG techniques. Your role will involve collaborating with cross-functional teams to seamlessly integrate AI models into platforms, ensuring scalability, accuracy, and efficiency. Additionally, you will support training and development programs across various locations in India, including client sites, academic institutions, and partner locations. Your responsibilities will include the continuous testing, refinement, and documentation of AI systems using tools such as Python, TensorFlow, Hugging Face, and cloud services. You will also be expected to engage in knowledge sharing activities, conduct technical workshops, and deliver on-site demos to promote AI solutions and drive adoption. This is a full-time position with benefits including cell phone reimbursement, provided meals, health insurance, paid sick time, and Provident Fund. The work schedule is during day shift hours. The ideal candidate should hold a Bachelor's degree and have a total of 1 year of experience, with specific experience as an AI Developer preferred. The work location for this role is in person. Join us in this exciting opportunity to contribute to cutting-edge AI projects and make a meaningful impact in the field of artificial intelligence.,

As an AI Specialist at our company based in Hyderabad, you will be responsible for training and fine-tuning LLMs such as LLaMA and Mistral to cater to company-specific use cases. You will play a vital role in customizing and optimizing model performance for seamless production deployment. Collaboration with internal teams for model integration and data pipelines will be a key aspect of your role. It is imperative that you stay abreast of the latest advancements in GenAI and LLM techniques to contribute effectively. To excel in this role, you must possess hands-on experience with LLMs and fine-tuning techniques. Your expertise in the specifics of vector database indexing will be highly beneficial. We are looking for someone with a robust background in advanced AI/ML techniques and database indexing, particularly in the context of production projects. Familiarity with technologies such as LoRA, QLoRA, RAG, and PEFT is desirable. Additionally, your knowledge of model evaluation, optimization, and GPU training will be crucial for success in this position.,

At InnovationM , we're shaping the future of enterprise AI and are looking for a Senior Agentic AI Engineer to lead the design and development of cutting-edge agentic frameworks. Youll help build a scalable AI foundation that empowers multiple teams to deploy intelligent agents with autonomy, memory, and reasoning capabilities. Key Skills: Python | LangGraph | CrewAI | RAG | LLMs | Agentic Frameworks Tool Integration | Vector Databases | Autonomous Decision-Making Human-in-the-Loop | Secure, Scalable Architectures What Youll Do: Architect enterprise-grade AI frameworks Build reusable agentic patterns using LangGraph, CrewAI, AutoGPT Enable tools like APIs, vector stores, RPA, and internal services Collaborate across teams to bring autonomy into complex workflows Mentor and guide teams on the future of agentic AI Why Join Us? Work on the latest in AI/ML and agentic systems Engage with large-scale clients and impactful projects Thrive in a culture of innovation, learning & development Location: Noida Sec-126 l 5 Days work from Office Apply now: neha.sharma@innovationm.com

Position : Machine Learning Engineer - Generative AI / LLMs (Onsite - Bengaluru) Experience : 3+ years of industry experience in ML, software engineering, and data engineering. Education : Masters degree or equivalent experience in Machine Learning. Location : Bangalore (HSR Layout) Job Description: We are looking for a talented Machine Learning Engineer to join our AI team at our Bengaluru office (Onsite Only). In this role, you will work on cutting-edge solutions leveraging Generative AI, Large Language Models (LLMs), NLP, and Computer Vision to solve complex real-world problems. Responsibilities: Design, build, and deploy ML models for NLP, Computer Vision, LLMs, and Generative AI use cases. Develop and maintain robust, scalable ML pipelines for training, evaluation, and deployment. Optimize model performance using cloud-based GPU resources and best practices. Implement scalable inference systems, A/B testing, and monitor production models. Collaborate with cross-functional teams to deliver AI-driven product features. Follow best practices in MLOps, LLMOps, Kubernetes, and Docker. Required Skills: Strong knowledge of Machine Learning, Deep Learning, NLP, and LLMs. Experience with Python, PyTorch, TensorFlow. Familiarity with Generative AI frameworks: Hugging Face, LangChain, MLFlow, LangGraph, LangFlow. Cloud platforms: AWS (SageMaker, Bedrock), Azure AI. Databases: MongoDB, PostgreSQL, Pinecone, ChromaDB. MLOps tools, Kubernetes, Docker. Preferred Qualifications: 3+ years of experience in ML/AI product development. Proven experience building and deploying NLP, LLM, and Generative AI solutions. Experience working with LLMOps best practices. Strong programming skills in Python and familiarity with JavaScript. Interested candidates kindly share your CV and below details to usha.sundar@adecco.com 1) Present CTC (Fixed + VP) - 2) Expected CTC - 3) No. of years experience - 4) Notice Period - 5) Offer-in hand - 6) Reason of Change - 7) Present Location -

As an NLP Lead Data Scientist, you will be building solutions that require analysing and transforming natural language data into useful outcomes using NLP techniques. To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods and text representation techniques and language models, consulting experience in FS, banking domain, good communication and client handling skill. Responsibilities : Build Solutions that identify intent and entities, other features from user comments, chat transcript and other unstructured text data. Design and implement advanced solutions utilizing NLP traditional Models and Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Train and fine-tune pre-trained NLP models and run evaluation experiments. Perform statistical analysis of results and refine models. Basic logical pseudo code writing. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and the ability to work effectively in a team environment. Primary skills: Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. AND/OR Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git Domain Skill: Consulting experience with FS,Banking domain for at least 3 years. Required qualifications: 16-20 years into Deep Learning framewokrs like Keras, Pytorch, TensorFlow Experience of design, building and deployment of ML/NLP Solutions Proficient in Python & SQL Experience in NLP tools like Genism, spacy, Stanford NLP, HuggingFace Must have excellent project/program management skills and have experience managing multiple work streams and projects at one time Have business acumen to manage revenues profitably and meet financial goals consistently. Able to quantify business value for clients and create win-win commercial propositions. Preferred qualifications: Experience automating data within Tableau/Qlik/ggplot/Shiny to tell a story through interactive visualizations Client relationship management: Build deep client relationship, network & be a thought partner. Anticipate business problems & deliver par excellence. Sales Support & account growth: Actively focus on opportunities to grow the client along with the senior engagement manager. Support the sales team as required for RFPs and regular sales pitches Firm building: Contribute to firm growth by participating and conducting training sessions. Coaching & grooming: Coach & groom the team on gaining knowledge & skills on first principles of analytics techniques, problem-solving, project management, client relationship management EDUCATION: B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent

Role & responsibilities Design and implement AI agent workflows. Develop end-to-end intelligent pipelines and multi-agent systems (e.g., LangGraph/LangChain workflows) that coordinate multiple LLM-powered agents to solve complex tasks. Create graph-based or state-machine architectures for AI agents, chaining prompts and tools as needed. Build and fine-tune generative models. Develop, train, and fine-tune advanced generative models (transformers, diffusion models, VAEs, GANs, etc.) on domain-specific data. Deploy and optimize foundation models (such as GPT, LLaMA, Mistral) in production, adapting them to our use cases through prompt engineering and supervised fine-tuning. Develop data pipelines. Build robust data collection, preprocessing, and synthetic data generation pipelines to feed training and inference workflows. Implement data cleansing, annotation, and augmentation processes to ensure high-quality inputs for model training and evaluation. Implement LLM-based agents and automation. Integrate generative AI agents (e.g., chatbots, AI copilots, content generators) into business processes to automate data processing and decision-making tasks. Use Retrieval-Augmented Generation (RAG) pipelines and external knowledge sources to enhance agent capabilities. Leverage multimodal inputs when applicable. Optimize performance and safety. Continuously evaluate and improve model/system performance. Use GenAI-specific benchmarks and metrics (e.g., BLEU, ROUGE, TruthfulQA) to assess results, and iterate to optimize accuracy, latency, and resource efficiency. Implement safeguards and monitoring to mitigate issues like bias, hallucination, or inappropriate outputs. Collaborate and document. Work closely with product managers, engineers, and other stakeholders to gather requirements and integrate AI solutions into production systems. Document data workflows, model architectures, and experimentation results. Maintain code and tooling (prompt libraries, model registries) to ensure reproducibility and knowledge sharing. Education: Bachelors or Master’s degree in Computer Science, Data Science, Artificial Intelligence. Programming proficiency: Expert-level skills in Python experience in machine learning and deep learning frameworks (PyTorch, TensorFlow). Generative model expertise: Demonstrated ability to build, fine-tune, and deploy large-scale generative models Familiarity with transformer architectures and generative techniques (LLMs, diffusion models, GANs) Experience working with model repositories and fine-tuning frameworks (Hugging Face, etc.). LLM and agent frameworks: Strong understanding of LLM-based systems and agent-oriented AI patterns. Experience with frameworks like LangGraph/LangChain or similar multi-agent platforms. AI integration and MLOps: Experience integrating AI components with existing systems via APIs and services. . Proficiency in retrieval-augmented generation (RAG) setups, vector databases,Familiarity with machine learning deployment and MLOps tools (Docker, Kubernetes, MLflow, KServe, etc.) Familiarity with GenAI tools: Hands-on experience with state-of-the-art GenAI models and APIs (OpenAI GPT, Anthropic, Claude, etc.) and with popular libraries (Hugging Face Transformers, LangChain, etc.). Awareness of the current GenAI tooling ecosystem and best practices.

We are seeking a dynamic and technically strong AI Lead with 68 years of industry experience, including a minimum of 5 years in AI/ML and Conversational AI technologies, with a specific focus on Microsofts AI ecosystem. The ideal candidate will lead the design, development, and delivery of intelligent solutions using Azure OpenAI, Copilot Studio, Microsoft Bot Framework, and AI Foundry. The individual will act as a hands-on technical lead, collaborating closely with product teams, architects, and business stakeholders to build impactful AI-powered copilots, chatbots, and enterprise automation solutions. Key Responsibilities: Lead end-to-end technical implementation of AI-driven projects using Microsoft AI tools: Azure OpenAI, Copilot Studio, and Bot Framework. Design and develop intelligent copilots, multi-turn chatbots, and custom GPT solutions integrated within enterprise tools such as Microsoft Teams, SharePoint, and Dynamics 365. Translate business requirements into technical architecture and AI flows using OpenAI APIs, prompt engineering, and integration with enterprise systems. Leverage AI Foundry to manage the AI lifecycle including model selection, deployment, monitoring, and optimization. Architect AI/ML solutions that use Retrieval-Augmented Generation (RAG), semantic search, and contextual memory frameworks (LangChain, Semantic Kernel, etc.). Collaborate with product owners and business analysts to identify high-value use cases and define solution roadmaps. Develop and execute POCs and MVPs with hands-on coding, configuration, and orchestration of LLMs and chatbot pipelines.Integrate with enterprise data sources via APIs, GraphQL, and Microsoft Graph to create holistic user experiences. Mentor junior developers and work with DevOps teams to ensure stable deployment, CI/CD, and performance monitoring. Create documentation and reusable components/templates for repeated use across the organization. Stay current on Microsofts AI advancements and recommend tools, features, or practices that improve time-to-value and performance. Must-Have Skills: 6-8 years of overall experience, including 5+ years in AI/ML or Conversational AI Deep hands-on knowledge of: Azure OpenAI services and APIs Copilot Studio for building Microsoft 365-integrated assistants Microsoft Bot Framework SDK/Composer for chatbot development Prompt engineering for LLM optimization Strong Python or Node.js development skills (for AI orchestration and integration) Experience with enterprise system integration using APIs (Microsoft Graph, REST, JSON, OAuth) Familiarity with Azure ML, Azure Cognitive Services, and Azure DevOps Ability to design RAG-based architectures, manage embeddings, and leverage vector databases (e.g., Azure AI Search) Strong understanding of natural language processing (NLP) and foundational models (GPT, BERT) Excellent communication, leadership, and stakeholder engagement capabilities Good-to-Have Skills: Experience with Semantic Kernel or LangChain Working knowledge of AI Foundry for orchestrating AI pipelines Familiarity with Copilot extensibility and Teams App Studio Exposure to M365 Copilot APIs and custom plugin creation Knowledge of Responsible AI, data security, and compliance principles Familiarity with containerized deployment (Docker, Kubernetes)Experience in building dashboards and analytics (Kibana, Grafana) to visualize bot usage and performance Basic understanding of Power Platform (Power Automate, Power Apps) and its integration with AI

Job Responsibilities We are seeking a highly strategic and execution-driven person to join the CEO's office as a (Program and Strategy Manager) and drive the adoption of Agentic AI (autonomous, goal-driven AI systems) across all functionsProduct, Tech, Marketing, Data, Sales, Customer Success, Delivery, Onboarding, HR, Finance, PR, Branding and more. You will act as a bridge across cross-functional teams to ensure alignment and drive the strategic direction of our AI-powered product portfolio. What will you do Cross-Functional Agentic AI Transformation Define and execute the company-wide high-impact agentic AI automation across functions.(e.g., AI-driven sales bots, automated customer onboarding, HR talent matching, finance forecasting). Develop metrics and KPIs to track AI-driven efficiency gains. Lead no-code AI tooling initiatives (e.g., GPT-based automation, AI agents, RPA, AutoML) to empower non-technical teams. Partner with Engineering & Data teams to integrate AI into existing workflows. Program Management and Strategy Develop, implement, and monitor key strategic initiatives that align with the company's overall business objectives. Define, track, and own key business KPIs, ensuring execution of high-impact priorities. Design and lead cross-functional projects to drive business outcomes, such as revenue growth, customer acquisition, and operational efficiency Prepare executive reports, investor decks, and MBR presentations. Provide strategic assistance and support to the senior leadership team Team & Stakeholder Management Act as the bridge between the CEO's Office and department heads to drive AI adoption. Conduct workshops to upskill teams on AI tools and best practices. Manage vendor partnerships (OpenAI, Microsoft, Google AI, etc.) for AI tooling. What you must have 3+ years of experience, preferably in Product, Program Management, or Strategy roles. Expertise in analytics, excel, SQL, and BI tools (Tableau, Looker, Power BI, etc.) Basic familiarity with LLM APIs (e.g., OpenAI, Anthropic, Hugging Face) Technical background with ability to collaborate effectively with ML/AI engineering teams. Exceptional communication skills to explain technical AI concepts to non-technical stakeholders. Excellence in strategic thinking, problem-solving, and decision-making. Analytical mindset with the ability to define and measure success metrics. Ability to thrive in a fast-paced, ambiguous environment.

Build and own the full voice bot pipeline including ASR, NLU, dialog management, tool calling, and TTS. Architect systems using MCP to connect ASR, memory, APIs, and LLMs in real-time. Implement RAG to ground responses using data from knowledge bases, inventory, and FAQs. Design scalable vector search systems for memory embedding and FAQ handling. Engineer low-latency ASR and TTS pipelines, optimizing for natural turn-taking. Apply fine-tuning, LoRA, and instruction tuning to reduce hallucinations and align model tone. Build observability systems and QA pipelines to monitor calls and analyze model behavior. Collaborate with cross-functional teams to scale the voice bot to thousands of users. Design modular, observable, and resilient AI systems. Implement retrieval pipelines, function calls, and prompt chaining across workflows. Expertly chunk, embed, and retrieve documents in RAG systems. Debug latency issues and optimize for low round-trip time. Trace hallucinations to root causes and fix via guardrails or tool access. Build prototypes using open-source or hosted tools with speed and flexibility. 5+ years in AI/ML or voice/NLP with real-time experience. Deep knowledge of LLM orchestration, vector search, and prompt engineering. Experience with ASR (Whisper, Deepgram), TTS (ElevenLabs, Coqui), and OpenAI models. Skilled in latency optimization and real-time audio pipelines. Hands-on with Python, FastAPI, vector DBs, and cloud platforms.

Core Responsibilities Model development Build and fine-tune image classification, detection, segmentation, OCR, and cross-modal retrieval pipelines in PyTorch or TensorFlow. Vision-language research transfer Re-implement recent conference papers; run ablation studies; compare checkpoints on COCO, LVIS, and internal datasets. Training and evaluation Write efficient trainers, manage experiment tracking (Weights & Biases / MLflow), and track metrics such as mAP, BLEU, CIDEr. Deployment Package models for REST and on-device endpoints (TorchScript, TensorRT); measure latency, memory, and accuracy. Code quality & collaboration Maintain clean repositories, contribute to design reviews, and present findings to non-AI colleagues and clients. Ethics & security Flag dataset bias, ensure privacy compliance, and document model limitations. Minimum Requirements Area Expectation Education B.Tech / M.Tech in CS, or related field. Python expertise 3+ years building deep-learning pipelines; solid OOP and unit testing. Frameworks PyTorch (preferred) or TensorFlow; OpenCV; experience with Hugging Face or similar libraries. Vision-language Hands-on with at least one of CLIP, BLIP, Segment-Anything, Detic, LLaVA, or similar. Tools Git, Docker, Linux, CUDA; basic CI/CD. Soft skills Clear written and spoken English; able to translate technical results into client-friendly summaries.

Role: AI Agent and GenAI Developer Responsibilities: Build and deploy Gen AI applications using LLMs, prompt engineering, and RAG frameworks. Hands-on with prompt engineering, RAG, LLM fine-tuning, and deployment workflows. Implement AI-driven solutions for analyzing, understanding, and migrating legacy codebases. Utilize AI tools to analyze complex legacy systems, identify business logic, dependencies, and potential risks associated with migration. Integrate APIs like OpenAI, Claude, Azure OpenAI, etc., into products or tools. Develop reusable components for prompt handling, embeddings, vector search, etc. Stay current with AI trends and tools Preferred candidate profile

Dear Candidate, We at TATA Technologies looking for an experienced candidate for Gen AI/ML lead role for Pune location. Please check the below JD, if matches to your profile please share your resume on nikhil.agale@tatatechnologies.com Job Title: Gen AI/ML Lead Total Experince: 6-8 Years Location: Pune Notice Period: Immediate-30 Days Role & responsibilities: Define and lead the Gen AI/ML strategy, aligning with organizational goals. Architect and oversee the development of intelligent chatbots for HR, Finance, and People Supply Chain functions. Lead initiatives to integrate in-context AI capabilities into existing applications to enhance user experience and productivity. Drive the development and deployment of Agentic AI solutions for autonomous and decision-support systems. Mentor and guide the AI/ML team, fostering innovation and collaboration. Collaborate with stakeholders to understand business needs and translate them into AI/ML solutions. Stay updated on the latest advancements in AI/ML to ensure cutting-edge implementations. Qualifications: Bachelors degree in computer science, Artificial Intelligence, Machine Learning, or related field. 6+ years of overall experience in SW development, with at least 3 years in a AI/ML development leadership role. Proven expertise in chatbot development, NLP, and contextual AI technologies. Strong understanding of ML frameworks (TensorFlow, PyTorch) and cloud AI services (AWS, Azure, Google Cloud). Exceptional problem-solving and strategic thinking abilities. Excellent communication and stakeholder management skills. Generative AI, Azure OpenAI Service, Azure Cognitive Search / Azure Search Service Preferred Technical Skills: Vector Database, Embeddings (OpenAI / Azure-based), ChatGPT / GPT-4 / GPT Models, Retrieval-Augmented Generation (RAG), LangChain, RESTful API development, OpenAI API, Prompt Engineering, Azure Machine Learning (Azure ML), Azure DevOps (ADO)Kubernetes / Docker (for AI microservices, Git & CI/CD Pipelines, Experience with cloud-native architecture (preferably in Azure), Experience leading AI engineering teams

Role and Responsibilities Develop and fine-tune LLMs using techniques like RAG, transfer learning, or domain-specific adaptation Build AI agents using frameworks like LangChain or CrewAI to manage dynamic and multi-step workflows Work with vector databases (e.g., Pinecone) to enable semantic search and retrieval Design and maintain ETL pipelines and ensure smooth data preprocessing and transformation Implement NLP solutions for tasks like intent detection, sentiment analysis, and content generation Develop backend APIs and services using Python frameworks like FastAPI or Flask Contribute to scalable microservice-based architectures Requirements Bachelor's degree in Computer Science, Information Technology, or a related field. 2 to 4 years in AI/ML development and backend system Machine Learning Fundamentals: Strong grasp of algorithms, model training, evaluation, and tuning Generative AI Models: Experience working with LLMs, RAG architecture, and fine-tuning techniques LangChain or Similar Frameworks: Hands-on experience building AI workflows using toolkits like LangChain Natural Language Processing (NLP): Proficiency in text analytics, classification, tokenization, embeddings Vector Databases: Practical use of tools like Pinecone, FAISS, or similar for retrieval-augmented generation Big Data Handling: Ability to work with large datasets, optimize storage, and processing pipelines SQL/NoSQL: Experience in querying and managing structured and unstructured data Python & API Development: Proficiency in Python and frameworks like FastAPI or Flask ETL & Data Preprocessing: Strong understanding of building pipelines for clean and efficient data processing Soft Skills: Strong problem-solving, communication, and collaboration abilities Good-to-Have Skills: Agentic AI Tools: Exposure to CrewAI or similar platforms for orchestrating multi-agent interactions Content Structuring: Experience in clustering, topic modeling, or organizing unstructured data ETL Enhancements: Advanced optimization techniques for faster and more efficient pipelines Domain Exposure: Prior work on projects involving customer insights, chat summarization, or sentiment analysis Role & responsibilities

Job Title: AI Engineer Job Type: Contract Location: Offshore (Remote) Start Date: July 28th, 2025 Experience: 5+ Years Shift Time: Till 1 pm EST Duration: 18 weeks Job Responsibilities: Design and implement scalable Gen AI solutions on Azure to meet enterprise needs. Build and optimize AI-based search systems for content discovery and business use cases. Develop agentic AI frameworks capable of autonomous decision-making and task execution. Work on data and content refinement pipelines to improve model performance and output relevance. Collaborate with cross-functional teams including architects, data scientists, and DevOps engineers. Ensure best practices in AI governance, model monitoring, and security are followed. Qualifications Gen AI on Azure (Azure OpenAI, Azure ML, Cognitive Services) Generative AI-based search (e.g., vector search, RAG models, embeddings) Strong foundation in AI/ML principles Experience with data/content pipelines and processing Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow) Preferred Experience: Proven track record in building agentic AI solutions Ability to work independently in a remote setting Experience in delivering short-term, high-impact AI projects

Were Hiring | Python Developer – Generative AI Location: Pune/Hyderabad Experience: 4–5 Years Join Us at the Cutting Edge of AI Innovation! Are you passionate about building products powered by Generative AI and LLMs? Do you enjoy working with cutting-edge tools like OpenAI, LangChain, and vector databases to bring AI ideas to life? We’re looking for a Python Developer (GenAI) who is ready to innovate, collaborate, and help us scale real-world AI solutions from prototype to production. Key Responsibilities: • Build scalable Python applications leveraging LLMs, prompt engineering, and RAG pipelines • Develop REST APIs using FastAPI/Flask for GenAI applications • Collaborate across teams to deploy LLM-powered tools (chatbots, assistants, summarizers) • Work with frameworks like LangChain, Hugging Face, and vector DBs like Pinecone, FAISS • Write clean, modular code with performance optimization in mind Skills We’re Looking For: • 4–5 years in Python development • Proven experience building LLM-based applications • Familiarity with OpenAI, Anthropic, Hugging Face, LangChain • Strong knowledge of REST APIs, microservices, and prompt engineering • Exposure to Git, CI/CD workflows, and agile environments Nice-to-Have: • Cloud exposure (AWS, Azure, GCP) • Experience with Docker/Kubernetes • Understanding of RAG pipelines, semantic search, or fine-tuning models Interested or know someone who fits? Drop your resume or referrals in the comments or send us a message! Thanks Dan - Dan@therxcloud.com

We are hiring an AI/ML Lead with hands-on experience in LLMs, RAG pipelines, prompt engineering, model fine-tuning/quantization, and Agentic AI. Youll work on building production-grade AI systems, lead technical strategy, and collaborate with cross-functional teams to deliver intelligent solutions. Key Skills: LLM evaluation & deployment (GPT, LLaMA, Mistral, etc.) RAG pipeline design (LangChain, vector DBs) Prompt engineering & chaining Fine-tuning, LoRA, quantization (INT4/INT8) Agentic AI system development Python, Hugging Face, PyTorch intha jd

Role & responsibilities Develop and fine-tune LLMs using techniques like RAG, transfer learning, or domain-specific adaptation Build AI agents using frameworks like LangChain or CrewAI to manage dynamic and multi-step workflows Work with vector databases (e.g., Pinecone) to enable semantic search and retrieval Design and maintain ETL pipelines and ensure smooth data preprocessing and transformation Implement NLP solutions for tasks like intent detection, sentiment analysis, and content generation Develop backend APIs and services using Python frameworks like FastAPI or Flask Contribute to scalable microservice-based architectures Requirements Bachelor's degree in Computer Science, Information Technology, or a related field. 2 to 4 years in AI/ML development and backend system Machine Learning Fundamentals: Strong grasp of algorithms, model training, evaluation, and tuning Generative AI Models: Experience working with LLMs, RAG architecture, and fine-tuning techniques LangChain or Similar Frameworks: Hands-on experience building AI workflows using toolkits like LangChain Natural Language Processing (NLP): Proficiency in text analytics, classification, tokenization, embeddings Vector Databases: Practical use of tools like Pinecone, FAISS, or similar for retrieval-augmented generation Big Data Handling: Ability to work with large datasets, optimize storage, and processing pipelines SQL/NoSQL: Experience in querying and managing structured and unstructured data Python & API Development: Proficiency in Python and frameworks like FastAPI or Flask ETL & Data Preprocessing: Strong understanding of building pipelines for clean and efficient data processing Soft Skills: Strong problem-solving, communication, and collaboration abilities

Key Responsibilities AI Architect Designs and oversees the AI strategy, ensuring solutions are scalable, adaptable, and aligned with business objectives. They establish AI frameworks, integrate systems, and provide guidance on infrastructure. AI Engineering Develops and deploys AI models, optimizing performance and ensuring seamless integration into existing workflows. They fine-tune algorithms, uses methods like RAG, Vector Databases and focus on real-world implementation. Develops and executes test plans to validate AI models, identifying performance issues and potential biases. Design and Development: Develop AI models and algorithms tailored to the specific needs of the business. Experience with Natural Language Processing (NLP), prompt engineering, etc. Works with existing data science team where applicable. AI Testing & Validation Responsibilities include: Ensure AI solutions perform reliably and ethically. Quality Assurance Conducts functional and non-functional testing, ensuring AI applications meet performance, security, and scalability requirements. Data Validation Monitors training data quality, ensuring accuracy, integrity, and consistency while minimizing errors and biases. Model Evaluation Assesses AI models through rigorous validation techniques, including cross-validation and error analysis, to refine performance. AI Ethics Auditing– Reviews AI decisions for fairness, transparency, and compliance with regulations, adjusting models where necessary. Deployment: Experience deploying models into production environments and working with teams to integrate solutions into existing software applications and platforms. Familiarity with CI/CD pipelines. Data Analysis: Analyze large datasets to extract meaningful insights and patterns; including interoperable data that may not be fully first party data. Strong understanding of supervised/unsupervised learning, neural networks, model evaluation and handling data at scale. Optimization: Have a passion for continual learning, optimizing AI models for performance and accuracy. Research: Stay updated with the latest AI advancements and integrate cutting-edge technologies into projects. Collaboration: Work closely with cross-functional teams to understand business requirements and deliver effective solutions. Documentation: Prepare comprehensive documentation for developed AI models and algorithms. Testing: Conduct rigorous testing and validation to ensure robustness and reliability of AI solutions. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or in related field. Experience: 5 to 8+ years of professional experience in software engineering, machine learning, or AI. 3+ years specifically working with generative AI models (e.g., transformers, diffusion models, LLMs like GPT, image generation models like Stable Diffusion or DALL•E). Technical Skills: Proficiency in programming languages such as Python, Java, C++, and frameworks like TensorFlow, PyTorch or Tensorflow and ML frameworks. Proficient in LLM Frameworks such as LangChain, LlamaIndex, OpenAI API. Analytical Skills: Strong analytical and problem-solving skills. Communication: Excellent verbal and written communication skills. Team Player: Ability to work collaboratively in a team environment and mentor junior developers. Creativity: Ability to think creatively and develop innovative solutions. Preferred Skills and Experience Experience with cloud platforms such as AWS, Azure, or Google Cloud. Knowledge of big data technologies and databases. Familiarity with natural language processing (NLP) and computer vision. Understanding of software development lifecycle and agile methodologies. Experience with version control systems like Git.