53 Retrieval-Augmented Generation Jobs

Job Title: Full Stack Developer Experience Required: 4+ Years Location: Onsite Role Summary We are seeking a skilled Full Stack Developer with hands-on experience in building scalable backend systems and intuitive frontend applications. The ideal candidate will have a strong foundation in modern web development, expertise in FastAPI, and exposure to GenAI infrastructures such as LangChain, Retrieval-Augmented Generation (RAG), and vector databases. This role is critical for developing client-facing GenAI interfaces as well as internal tools, dashboards, and annotation platforms. Key Responsibilities Backend Development: Design, build, and optimize backend systems using FastAPI. Integrate and manage vector databases (e.g., FAISS, Chroma) for retrieval workflows. Implement LangChain/RAG infrastructure for GenAI-powered applications. Ensure robust data persistence, API reliability, and scalability. Frontend & Tools Development: Build interactive dashboards, annotation tools, and PoC UIs for internal and client use. Create seamless, user-friendly web applications with responsive design. Collaborate with data scientists and product managers to translate requirements into intuitive interfaces. System Integration & Deployment: Develop and integrate APIs and microservices. Work with cloud platforms (AWS/GCP/Azure) for deployment and scaling. Ensure CI/CD pipelines and maintain DevOps best practices. Qualifications & Skills Must Have: 4+ years of full-stack development experience. Strong proficiency in Python (FastAPI) and JavaScript/TypeScript frameworks (React/Next.js preferred). Experience with vector databases (FAISS, Chroma, Pinecone, Weaviate). Knowledge of LangChain, RAG, and LLM-based application development. Hands-on experience with databases (SQL/NoSQL). Familiarity with cloud services and containerization (Docker, Kubernetes). Good to Have: Experience building annotation tools, dashboards, or data-centric UIs. Knowledge of data pipelines and model deployment workflows. Prior experience with GenAI/ML-powered applications. Role & responsibilities Preferred candidate profile

We are looking for a highly motivated AI Presales Intern to join our team. In this role, you will engage directly with enterprise customers to understand their needs, design tailored Generative AI solutions , and demonstrate how AI can create measurable business value. This position sits at the intersection of engineering, product, and sales , offering exposure to both technical solutioning and strategic business conversations. AI Presales Intern Location: Hyderabad Employment Type: Internship (with potential PPO based on performance) Key Responsibilities Collaborate with sales and product teams to gather customer requirements and design AI-powered solution architectures . Deliver compelling technical demos, workshops, and proofs-of-concept (POCs) using LLMs, RAG pipelines, and prompt engineering. Translate technical concepts into clear, business valuefocused narratives that resonate with both technical and executive stakeholders. Support enterprise clients in overcoming AI adoption challenges such as security, scalability, ROI, and compliance . Build and maintain presales assets including reference architectures, demo scripts, pitch decks, and technical documentation. Act as a bridge between engineering teams and business leaders , ensuring alignment and clarity. Required Skills Hands-on experience with Generative AI & LLMs (fine-tuning, Retrieval-Augmented Generation, prompt engineering). Proficiency in Python programming (APIs, frameworks, and problem-solving). Familiarity with AI frameworks like LangChain, Hugging Face, OpenAI APIs . Excellent communication, presentation, and storytelling abilities . Proven ability to explain complex AI concepts to both technical and non-technical stakeholders. Strong demonstration skills , with the ability to showcase ROI through real-world use cases. High IQ & EQ : strong curiosity, active listening, and the ability to ask the right questions at the right time. Preferred/Teachable Skills Strategic & Business Acumen : understanding of enterprise AI adoption challenges (security, compliance, scalability). Solution Architecture & Integration : exposure to enterprise systems, APIs, and cloud environments. Awareness of go-to-market strategies and customer enablement practices. What Youll Gain Hands-on experience designing and delivering enterprise-grade AI solutions . Direct exposure to client interactions, workshops, and presales strategy . Mentorship from senior AI, product, and presales professionals. Opportunity for conversion to a full-time AI Presales Engineer role based on performance. If you believe you are qualified and are looking forward to setting your career on a fast-track, apply by submitting a few paragraphs explaining why you believe you are the right person for this role. To know more about Techolution, visit our website: www.techolution.com If you believe you are qualified and are looking forward to setting your career on a fast-track, apply by submitting a few paragraphs explaining why you believe you are the right person for this role.To know more about Techolution, visit our website: www.techolution.com About Techolution: Techolution is a next gen AI consulting firm on track to become one of the most admired brands in the world for "AI done right". Our purpose is to harness our expertise in novel technologies to deliver more profits for our enterprise clients while helping them deliver a better human experience for the communities they serve. At Techolution, we build custom AI solutions that produce revolutionary outcomes for enterprises worldwide. Specializing in "AI Done Right," we leverage our expertise and proprietary IP to transform operations and help achieve business goals efficiently. We are honored to have recently received the prestigious Inc 500 Best In Business award , a testament to our commitment to excellence. We were also awarded - AI Solution Provider of the Year by The AI Summit 2023, Platinum sponsor at Advantage DoD 2024 Symposium and a lot more exciting stuff! While we are big enough to be trusted by some of the greatest brands in the world, we are small enough to care about delivering meaningful ROI-generating innovation at a guaranteed price for each client that we serve. Our thought leader, Luv Tulsidas, wrote and published a book in collaboration with Forbes, Failing Fast Secrets to succeed fast with AI. Refer here for more details on the content - https://www.luvtulsidas.com/ Let&aposs explore further! Uncover our unique AI accelerators with us: 1. Enterprise LLM Studio : Our no-code DIY AI studio for enterprises. Choose an LLM, connect it to your data, and create an expert-level agent in 20 minutes. 2. AppMod. AI : Modernizes ancient tech stacks quickly, achieving over 80% autonomy for major brands! 3. ComputerVision. AI : Our ComputerVision. AI Offers customizable Computer Vision and Audio AI models, plus DIY tools and a Real-Time Co-Pilot for human-AI collaboration! 4. Robotics and Edge Device Fabrication : Provides comprehensive robotics, hardware fabrication, and AI-integrated edge design services. 5. RLEF AI Platform : Our proven Reinforcement Learning with Expert Feedback (RLEF) approach bridges Lab-Grade AI to Real-World AI. Some videos you wanna watch! Computer Vision demo at The AI Summit New York 2023 Life at Techolution GoogleNext 2023 Ai4 - Artificial Intelligence Conferences 2023 WaWa - Solving Food Wastage Saving lives - Brooklyn Hospital Innovation Done Right on Google Cloud Techolution featured on Worldwide Business with KathyIreland Techolution presented by ION Worlds Greatest Visit us @ www.techolution.com : To know more about our revolutionary core practices and getting to know in detail about how we enrich the human experience with technology. Show more Show less

About the Role: We are seeking a passionate and skilled Developer with hands-on experience in Generative AI technologies to join our growing engineering team. This role is ideal for someone who thrives on building scalable backend systems while integrating cutting-edge AI capabilities into enterprise applications. Key Responsibilities: Design, develop, and maintain backend services and APIs using modern frameworks (e.g., Java Spring Boot, Node.js, or Python FastAPI). Integrate and deploy Generative AI models (e.g., OpenAI, Hugging Face, LangChain ) into production environments. Fine-tune and optimize LLMs for specific use cases. Build secure, scalable, and high-performance microservices. Monitor and improve system performance, reliability, and scalability. Implement CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Deploy and manage applications on cloud platforms, preferably Microsoft Azure. Participate in code reviews, testing, and continuous integration processes. Required Skills & Qualifications: 3+ years of backend development experience using Java Spring Boot or Python. Strong understanding of RESTful APIs, microservices architecture, and asynchronous processing. Experience working with Generative AI APIs and/or open-source models . Experience with LangChain, LLM orchestration, or RAG (Retrieval-Augmented Generation) pipelines. Familiarity with prompt engineering , embedding models, or vector databases . Strong problem-solving and debugging skills. Preferred Skills: Exposure to multi-modal AI systems and agentic AI frameworks. Exposure to MLOps and model deployment workflows. Experience with Docker, Kubernetes, and CI/CD pipelines. Experience with cloud platforms (Azure, AWS or GCP). Knowledge of frontend frameworks like React or Angular.

About The Company BP Energy is a global leader in the energy sector, committed to delivering innovative and sustainable energy solutions. With a rich history of operational excellence and a focus on technological advancement, BP Energy is dedicated to transforming the future of energy through cutting-edge innovation, responsible practices, and a commitment to reducing carbon emissions. The company fosters a dynamic and inclusive work environment that encourages continuous learning and professional growth, aiming to create value for stakeholders while contributing positively to society and the environment. About The Role We are seeking a highly experienced and visionary Staff AI Engineer to join BP Energy&aposs AI Acceleration organization. This role is pivotal in designing, developing, and deploying scalable AI-powered applications that provide tangible business value. The ideal candidate will possess a deep understanding of modern AI tooling, infrastructure, and disciplined software engineering principles. You will lead initiatives that involve building foundational AI platforms, integrating advanced AI models, and automating workflows to enhance operational efficiency and innovation across the enterprise. In this role, you will collaborate closely with cross-functional teams including data scientists, product managers, and business stakeholders to translate complex technical ideas into impactful solutions. You will also provide technical mentorship, influence architectural decisions, and champion best practices in responsible AI deployment. This position offers an exciting opportunity to shape the future of AI at BP Energy, working on high-impact projects that drive real-world results and sustainability initiatives. Qualifications Required: 12+ years of professional software engineering experience with a proven track record of designing and deploying sophisticated systems in production environments. Strong programming skills in Python (preferred), Java, or similar languages, with extensive experience in developing microservices, APIs, and backend architectures. Deep understanding of software architecture, cloud infrastructure (AWS, Azure, GCP), and modern DevOps practices. Hands-on experience integrating machine learning models into production systems, including LLMs via APIs, fine-tuning, retrieval-augmented generation, embeddings, and agent-based frameworks. Comprehensive knowledge of large language models, vector-based search, unstructured data processing, and related AI technologies. Proven ability to work efficiently without compromising code quality, test coverage, or operational standards. Exceptional problem-solving skills, with a bias for action and the ability to navigate ambiguity and complexity effectively. Experience in technical mentorship and influencing cross-team initiatives. Excellent communication skills, capable of translating complex technical concepts into clear business insights. Preferred Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. Experience with GenAI frameworks like LlamaIndex, Crew AI, AutoGen, or similar agent orchestration tools. Background in building reusable ML components or contributing to internal ML platform development. Experience working in embedded or forward-deployed teams requiring rapid iteration and close collaboration with business units. Proficiency with Python and ML/data science libraries such as scikit-learn, pandas, NumPy, PyTorch, TensorFlow. Understanding of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, and statistical inference. Experience working with unstructured data types like documents, conversations, or images and transforming them into structured formats. Previous experience building chatbots, search engines, or generative AI interfaces. Background in platform engineering or internal developer tools teams is advantageous. Responsibilities Design, develop, and maintain production-grade AI applications and services, adhering to modern software engineering practices such as CI/CD, testing, observability, and cloud-native design. Define and implement foundational AI platforms, including conversational bots, AI-powered search, unstructured data processing, and GenAI solutions, ensuring reusability and scalability enterprise-wide. Lead architectural decisions, establishing guidelines for software development lifecycle, explainability, and responsible AI practices. Drive cross-functional initiatives with business stakeholders to rapidly develop and deploy AI solutions addressing high-priority challenges. Evaluate and integrate existing AI tools, frameworks, and APIs, including LLMs, vector databases, retrieval-augmented generation, and other relevant technologies. Champion automation across workflowsfrom data ingestion and preprocessing to model deploymentdefining success metrics and operational procedures. Partner with data scientists, product managers, and engineers to ensure end-to-end delivery, performance, and reliability of AI products. Stay abreast of emerging AI technologies, prioritizing practical applications that deliver tangible value. Contribute to internal knowledge bases, tooling libraries, and documentation to promote best practices organization-wide. Mentor engineering teams and data scientists, providing technical leadership and raising standards for rigor and impact. Benefits BP Energy offers a comprehensive benefits package designed to support the well-being and professional growth of our employees. This includes competitive salary packages, health insurance, retirement plans, and paid time off. We promote a flexible work environment with hybrid working arrangements to support work-life balance. Employees have access to continuous learning opportunities, technical training, and development programs. Additionally, BP Energy fosters an inclusive culture that values diversity, innovation, and collaboration, providing a platform for employees to thrive and make meaningful contributions to the future of energy. Show more Show less

Job Summary: We are seeking an innovative and highly skilled Data Scientist (LLM & Generative AI) with 5+ years of experience in machine learning, natural language processing, and applied AI. The ideal candidate will have deep expertise in large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and agentic AI approaches. This role involves developing intelligent, autonomous, and scalable AI solutions that leverage cutting-edge research in generative AI, transformers, and multi-agent systems. In addition, the candidate will be expected to collaborate closely with engineering teams to bring research into production. Key Responsibilities: Research, design, and implement advanced LLM-based solutions for NLP, knowledge retrieval, and reasoning tasks. Develop and fine-tune LLMs (e.g., GPT, LLaMA, Falcon, Claude) for domain-specific use cases. Apply agentic AI approaches (multi-agent systems, autonomous agents, decision-making pipelines) to real-world business challenges. Design and implement retrieval-augmented generation (RAG) pipelines to combine structured/unstructured data with LLM capabilities. Build and optimize prompt engineering frameworks, evaluation metrics, and automated testing for generative AI outputs. Collaborate with ML engineers to deploy models into scalable cloud environments (AWS/GCP/Azure). Work with cross-functional teams to integrate LLM-powered agents into applications, workflows, and customer-facing products. Stay up-to-date with the latest research in LLMs, generative AI, reinforcement learning, and agentic architectures. Mentor junior team members and contribute to building an internal knowledge base on applied AI best practices. Requirements: Must-Have Skills: 5+ years of experience in data science, ML, or AI research with a focus on NLP and deep learning. Strong experience working with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on expertise in fine-tuning and deploying LLMs using frameworks like Hugging Face Transformers, LangChain, or Haystack. Deep understanding of agentic AI approaches, including orchestration, multi-agent workflows, and autonomous reasoning systems. Proficiency in Python and ML libraries (PyTorch, TensorFlow, Hugging Face, LangChain, Ray). Strong background in applied NLP techniques such as text classification, summarization, embeddings, semantic search, and dialogue systems. Experience building RAG pipelines with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus). Familiarity with MLOps and cloud deployment (AWS Sagemaker, GCP Vertex AI, Azure ML). Nice-to-Have Skills: Knowledge of reinforcement learning (RLHF, RLAIF) for LLM optimization. Experience with multi-modal models (text, image, speech). Familiarity with graph databases and knowledge graphs for reasoning tasks. Contributions to open-source projects in NLP/LLM space. Understanding of privacy, security, and ethical considerations in generative AI. Location- remote Salary -25lpa Experience -5+years 6 months contract (extendable) Show more Show less

Location: Hyderabad, India | Employment Type: Full-Time Experience Level: 4+Years Company: Covasant Contact Person: Ranjith Reddy 9703455109 | ranjith.palle@covasant.cm | linkedin.com/in/ranjith-r-75a766227 Build the Future of AI with Covasant At Covasant , we don't just work with AI we engineer the next era of it. We're hiring mid-level to senior developers and AI leads to help us build next-generation agentic AI systems that are intelligent, collaborative, and scalable. This is your chance to go beyond prompt engineering and shape the architecture of autonomous, multi-agent AI solutions using tools like LangGraph, AutoGen, CrewAI , and more. If youve got the skills and curiosity to work on what the AI world will be talking about next year , we want to hear from you. Your Role Design and develop multi-agent LLM systems using LangGraph, AutoGen, or CrewAI. Build and deploy MCP servers , LLM gateways , and design Agent-to-Agent collaboration flows. Fine-tune language models for verticals like healthcare, manufacturing, or finance. Architect retrieval-augmented generation (RAG) systems with vector stores like FAISS, Pinecone, or Weaviate. Integrate tools like LangSmith , GuardrailsAI , and knowledge graphs to ensure trust, safety, and observability. Collaborate cross-functionally with product, data science, and engineering teams. What You Bring 2+ years in software development, with strong Python skills. Proven expertise in one or more: LangGraph , AutoGen , CrewAI . Deep understanding of Agent-based AI , LLM orchestration , and RAG pipelines . Experience fine-tuning LLMs and applying prompt engineering and domain adaptation . Familiarity with tools like LangSmith , PromptGuard , or Guardrails frameworks. Bonus If You Have Cloud experience (AWS, Azure, GCP) Familiarity with Docker, Kubernetes Exposure to multi-modal models (LLaMA, Mistral, Falcon) Frontend tech: React, Angular, or Vue CI/CD, MLOps, or LLMOps knowledge Important Were currently hiring mid-level, senior, and lead professionals with hands-on experience in AI/ML projects . These openings are not for freshers or professionals with less than 2 years of experience but we are planning something exciting for early-career AI talent soon! Why Join Covasant Work on real-world agentic AI systems ahead of industry trends Collaborative and innovation-first work culture Competitive pay, benefits & performance incentives Hybrid/flexible work setup A chance to lead and influence the next chapter in AI Let’s Connect If this excites you — whether or not you're actively job hunting — don’t miss the chance to explore this game-changing opportunity. Ranjith Reddy – 9703455109 ranjith.palle@covasant.cm Connect with me on LinkedIn – I’d love to stay in touch, even if this isn’t the right time. Apply now or just start a conversation. The future of AI doesn’t wait — and neither should you.

Job Title: Senior Data Scientist AI/ML & GenAI Location: Gurugram Department: Data Intelligence Digital IT Reports To: Data Science Manager Role Overview We are looking for a highly skilled and intellectually curious Senior Data Scientist with 7+ years of experience in applying advanced machine learning and AI techniques to solve complex business problems. The ideal candidate will have deep expertise in Classical Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI (GenAI), along with strong hands-on coding skills and a proven track record of delivering impactful data science solutions. This role requires a blend of technical excellence, business acumen, and collaborative mindset. Key Responsibilities Design, develop, and deploy ML models using classical algorithms (e.g., regression, decision trees, ensemble methods) and deep learning architectures (CNNs, RNNs, Transformers). Build NLP solutions for tasks such as text classification, entity recognition, summarization, and conversational AI. Develop and fine-tune GenAI models for use cases like content generation, code synthesis, and personalization. Architect and implement Retrieval-Augmented Generation (RAG) systems for enhanced contextual AI applications. Collaborate with data engineers to build scalable data pipelines and feature stores. Perform advanced feature engineering and selection to improve model accuracy and robustness. Work with large-scale structured and unstructured datasets using distributed computing frameworks. Translate business problems into data science solutions and communicate findings to stakeholders. Present insights and recommendations through compelling storytelling and visualization. Mentor junior data scientists and contribute to internal knowledge sharing and innovation. Required Qualifications 7+ years of experience in data science, machine learning, and AI. Strong academic background in Computer Science, Statistics, Mathematics, or related field (Masters or PhD preferred). Proficiency in Python, SQL, and ML libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face). Experience with NLP and GenAI tools (e.g., Azure AI Foundry, Azure AI studio, GPT, LLaMA, LangChain). Hands-on experience with Retrieval-Augmented Generation (RAG) systems and vector databases. Familiarity with cloud platforms (Azure preferred, AWS/GCP acceptable) and MLOps tools (MLflow, Airflow, Kubeflow). Solid understanding of data structures, algorithms, and software engineering principles. Experience with Azure, Azure Copilot Studio, Azure Cognitive Services Experience with Azure AI Foundry would be a strong added advantage Preferred Skills Exposure to LLM fine-tuning, prompt engineering, and GenAI safety frameworks. Experience in domains such as finance, healthcare, retail, or enterprise SaaS. Contributions to open-source projects, publicatio s, or patents in AI/ML. Soft Skills Strong analytical and problem-solving skills. Excellent communication and stakeholder engagement abilities. Ability to work independently and collaboratively in cross-functional teams. Passion for continuous learning and innovation. Show more Show less

Location - Airoli, Mumbai Contract Duration - 9 months (Extendable to a year) Key Responsibilities: Design and implement scalable data intelligence platforms that integrate structured and unstructured data sources. Develop and fine-tune Generative AI models (LLMs, GANs, Diffusion Models) for tasks such as text generation, synthetic data creation, and content automation. Collaborate with data engineers, ML engineers, and product teams to deploy AI solutions into production environments. Build and maintain data pipelines , feature stores, and model monitoring systems. Apply prompt engineering techniques to optimize LLM performance for business use cases. Conduct experiments and A/B testing to evaluate model performance and business impact. Ensure compliance with data governance, privacy, and ethical AI standards. Expertise in AKS. Should be able to integrate the solution in current landscape. Required Qualifications: Bachelors or Masters degree in Computer Science, Data Science, AI, or related field. 3-5 years of experience in data science, machine learning, or AI engineering. Hands-on experience with LLMs (e.g., GPT, Claude, LLaMA) and frameworks like Hugging Face, LangChain, or OpenAI APIs. Proficiency in Python , SQL, and cloud platforms (AWS, Azure, or GCP). Strong understanding of data modeling , ETL processes , and MLOps . Experience with vector databases , embedding models , and retrieval-augmented generation (RAG) is a plus. Preferred Skills: Experience with knowledge graphs , semantic search , or data fabric architectures . Familiarity with AutoML , RLHF , or multi-modal AI . Excellent communication and stakeholder management skills. Show more Show less

Role: Senior Data Scientist -Digital CX Technical Lead - Gen AI Experience:8+years in Data Science Location: NCR/Bangalore Work Mode: Hybrid Shift Timing: 1:30 pm - 11:30pm Technical Skills Strong hands-on technical background with a solid understanding of conversational AI technologies, machine learning, natural language processing, and software development methodologies. Strong background in Natural Language Processing (NLP), deep learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG). Experience with deep learning frameworks like PyTorch or TensorFlow. Experience with cloud platforms (AWS, Azure, GCP) for deploying AI models. Strong understanding of neural networks, transformers, and reinforcement learning. Familiarity with software development best practices, version control (e.g., Git), and agile methodologies. Experience with CI/CD pipelines and DevOps practices. Excellent software development skills to drive the development and deployment of cutting-edge AI solutions Demonstrated leadership and team management skills, with the ability to inspire, guide, and develop a diverse team of professionals. Excellent problem-solving skills and the ability to think critically and creatively. Strong communication skills and the ability to work effectively in a team environment. Leadership qualities with a proactive and collaborative approach. BE/BTech/MCA/Ph.D. from tier I/II institute in CS, Mathematics or related field

Greetings from BMW Techworks India Role: Sr. Level Generative AI Engineer What awaits you! Join our team to industrialize sophisticated cutting-edge algorithms for our next generation of BMW Cars. The role involves designing, developing, and refining generative models that will form the core of our innovative AI-driven products and services. The ideal candidate will possess deep expertise in generative AI practices, with the ability to implement models that can synthesize novel content, ranging from text and images to complex data patterns. In your daily work, you will find yourself in an international and interdisciplinary environment with an agile mindset. Our campus offers the cloud infrastructure you need to work productively with large amounts of data and focus on the software for the automobile of the future. What should you bring along! 5+ years of experience in AI/ML research and development Experience and deepen knowledge about Generative AI Proven experience with generative model architectures such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and autoregressive models like Transformer-based networks, LLMs, SLMs, Knowledge about generative AI techniques and fine-tuning methods to improve model performance. Familiar with implementing RAG (Retrieval-Augmented Generation) architecture for sophisticated AI applications Extensive knowledge of multimodal models, foundation models, and fine-tuning techniques. In-depth understanding of transformer architectures, RAG architecture Basic knowledge of AI accelerator chips Knowledge of MLOps practices to ensure the robustness and reliability of AI systems Expertise in designing and implementing scalable and efficient AI systems Strong Python programming skills and experience with modern AI frameworks Excellent communication and collaboration skills, with the ability to lead and mentor junior team members Knowledge of software development processes in the automotive environment is advantageous Familiarity with cloud computing platforms and services for AI/ML (AWS) Business fluent knowledge of English (written and spoken)

Lead AI Engineer About the Role: We are seeking an experienced AI specialist with a strong Computer Science/Engineering background to design, develop, and deploy advanced Generative AI-based solutions. In this role, you will build intelligent AI agents, leverage graph-based RAG techniques, and ensure robust production deployments to solve complex challenges in the Architecture, Engineering, and Construction (AEC) domain. Key Responsibilities Collaborate with stakeholders to align AI initiatives with business goals. Lead and mentor a team of ML engineers and data scientists. Design, develop, and deploy enterprise-grade RAG systems that deliver accurate, context-aware responses in production environments. Incorporate AI agents and graph-based techniques (e.g., GraphRAG) to enable enhanced contextual data retrieval and support complex query relationships. Implement robust evaluation frameworks to measure and enhance RAG system effectiveness. Create scalable pipelines for document processing, embedding generation, and knowledge base management. Build monitoring systems to track performance, detect issues, and ensure RAG system reliability. Architect cloud-native solutions that can scale to handle enterprise document volumes and query loads. Explore and integrate cutting-edge techniques in Generative AI, including but not limited to model fine-tuning. Qualifications & Skills A strong foundation in Computer Science or Engineering with 5-10 years' experience in NLP, Computer Vision, Deep Learning, Machine Learning, or related field. Extensive experience with LLMs and related technologies (e.g., embedding models, vector databases, etc.). Proven expertise in developing production-grade RAG systems. Knowledge of graph-based RAG techniques (e.g., Graph RAG or alternatives). Proficiency in Python and familiarity with Generative AI frameworks such as Hugging Face, Lang Chain, Llama Index, Prompt flow, Auto Gen, etc. Hands-on experience with cloud-based AI deployments (Azure preferred). Experience in LLM fine-tuning and optimization (e.g., LoRA) is a plus. Exposure to multi-modal RAG systems and LLMOps frameworks. Familiarity with deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Tensorflow, etc.).

L&T is Hiring!!! Job Title: Generative AI Location: Bangalore Experience: 8 - 15 years Education: Masters or PhD in AI/ML, Data Science, or related field Key Skills & Responsibilities: Hands-on experience with GENA AI and RAG (Retrieval-Augmented Generation) implementations Expertise in LLM-based application development Strong knowledge of data vectorization, chunking, and embedding techniques Proven track record in AI/ML model development and deployment Ability to design scalable and efficient data science workflows

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS. Key Responsibilities: Lead the end-to-end technical architecture for consumer-facing digital platforms, ensuring robustness, scalability, and reusability (e.g., pricing engines, agent assist call center) Design and implement integration architectures connecting native apps, modern SaaS platforms, and legacy systems (e.g., PMS, ERP, booking engines). Define non-functional architecture requirements such as performance tuning, failover, caching, and throughput optimization to handle peak traffic loads. Establish architectural patterns (e.g., microservices, event-driven systems, API gateways) and code-level guardrails across teams. Architect foundational capabilities to support AI/Agentic applications - including context management, modular services, and workflow orchestration layers. Evaluate, integrate, and advise on enabling GenAI-based features (e.g., content generation, summarization, conversational interfaces). Review solution implementations for code quality, technical debt, and adherence to architectural standards. Lead cross-functional teams to deliver technical prototypes and scalable MVPs that demonstrate business value quickly. Provide technical mentorship to engineering teams across development, DevOps, and testing. Contribute to AI/GenAI strategy by identifying integration points for LLMs or NLP tools (e.g., content generation, knowledge retrieval, smart workflows). Preferred Experience: 8-11 years of experience in backend architecture, enterprise integration, or platform engineering, with a strong track record of designing scalable and high-performance systems. Deep hands-on expertise in cloud-native development (preferably AWS), distributed systems, and containerization technologies such as Docker and Kubernetes. Strong experience in microservices and event-driven architecture, with a focus on performance tuning, caching strategies, and system reliability under peak loads. Proven ability to integrate modern digital platforms (e.g., headless CMS, mobile SDKs) with legacy systems such as PMS, POS, and ERP, ensuring seamless interoperability. Solid grounding in performance engineering, including load balancing, latency reduction, and resilient system design. Exposure to GenAI/LLM integration using tools like OpenAI, Vertex AI, LangChain, or Retrieval-Augmented Generation (RAG) frameworks is a strong plus. Familiarity with personalization engines and/or platforms (e.g., Oracle, Adobe, Salesforce), and omnichannel architecture relevant to Travel, Hospitality, or CPG domains. Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client facing ZSers business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems-the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive. If you're eager to grow, contribute, and bring your unique self to our work, we encourage you to apply. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To complete your application: Candidates must possess or be able to obtain work authorization for their intended country of employment.An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At:

We are seeking a Tech Lead with expertise in AI/ML and Fullstack development to drive the development of core platform features. This role is instrumental in architecting and optimizing high-performance AI-driven applications, building robust microservices, and ensuring seamless integration across AI, backend, and frontend systems. You will lead the development of workflow automation modules, AI-powered search engines, and scalable platforms. Qualification: Bachelors/masters degree in computer science, AI, Machine Learning, or a related field. 7+ years of experience in AI/ML and fullstack development. Expertise in building AI-powered applications, leveraging LLMs, NLP, and deep learning models. Strong programming skills in Python, Java, Node.js, TypeScript. Deep understanding of cloud-based AI solutions (AWS, GCP, Azure). Experience in microservices, REST/WebSockets, and real-time API development. Strong knowledge of DevOps, MLOps, Kubernetes, and CI/CD pipelines. Experience in vector databases, RAG-based search, and AI-powered data retrieval. Responsibilities: Develop & Optimize Core AI/ML Features: Architect and implement AI-powered automation modules, search systems, and data retrieval models. Deploy LLM-driven applications using LangChain, RAG, and embedding-based techniques. Enhance workflow automation using Haystack, LangGraph, and Vector DBs. Lead Fullstack Platform Development: Design and build scalable microservices and event-driven architectures. Implement high-performance backend systems in Python, Java, and Node.js. Develop AI-integrated dashboards and frontend applications using React.js, Angular, and TypeScript. AI Model Deployment & DevOps: Deploy and monitor AI models on Kubernetes, OpenShift, and cloud platforms. Implement CI/CD pipelines, containerization, and scalable deployment strategies. Technical Leadership & Best Practices: Lead and mentor junior developers and AI engineers. Enforce best practices in software engineering, AI model deployment, and fullstack architecture.

We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! REQUIREMENTS: Total experience 5+ years. Proven experience working with Generative AI frameworks (OpenAI, Anthropic, etc.) Expertise in Generative AI and Retrieval-Augmented Generation (RAG). Hands-on experience with open-source AI libraries such as Hugging Face and TensorFlow. In-depth knowledge of NLP, deep learning architectures, and ML algorithms. Strong hands-on experience in Python (data processing, APIs, AI/ML libraries) Advanced knowledge of AWS services. Expertise in Prompt Engineering and LLM tuning. Experience with API development, CI/CD, and DevOps tools Exposure to MLOps practice s and frameworks Strong communication and teamwork skills, with the ability to mentor and collaborate effectively. RESPONSIBILITIES: Writing and reviewing great quality code Understanding the clients business use cases and technical requirements and be able to convert them in to technical design which elegantly meets the requirements Mapping decisions with requirements and be able to translate the same to developers Identifying different solutions and being able to narrow down the best option that meets the clients' requirements Defining guidelines and benchmarks for NFR considerations during project implementation Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it Understanding and relating technology integration scenarios and applying these learnings in projects Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Experience: 5-8 Years Work Mode: Pune & Hyderabad Job Type: Fulltime Mandatory Skills: Python, SQL, ETL, Numpy / Scikit-learn / Pandas, AI/ML, Gen AI, TensorFlow, PyTorch, AI frameworks like Autogen, Langgraph, CrewAI, Agentforce, Machine Learning, Predictive Machine Learning and LLM. Job Description We are seeking an experienced and driven Senior AI/ML Engineer with 5-8 years of experience in AI/ML Predictive ML, GenAI and Agentic AI. The ideal candidate should have a strong background in developing and deploying machine learning models, as well as a passion for innovation and problem-solving. Required Qualifications & Skills Bachelors or Masters degree in computer science / AIML / Data Science. 5 to 8 years of overall experience and hands-on experience with the design and implementation of Machine Learning models, Deep Learning models, and?LLM models for solving business problems. Proven experience working with?Generative AI technologies, including prompt engineering, fine-tuning large language models (LLMs), embeddings, vector databases (e.g., FAISS, Pinecone), and Retrieval-Augmented Generation (RAG) systems. Expertise in Python (NumPy, Scikit-learn, Pandas), TensorFlow, PyTorch,?transformers (e.g., Hugging Face), or MLlib. Experience in working on Agentic AI frameworks like Autogen, Langgraph, CrewAI, Agentforce etc Expertise in cloud-based data and AI solution design and implementation using?GCP / AWS / Azure, including the use of their Gen AI services. Good experience in building complex and scalable ML and?Gen AI?solutions and deploying them into production environments. Experience with scripting in SQL, extracting large datasets, and designing ETL flows. Excellent problem-solving and analytical skills with the ability to translate business requirements into data science and?Gen AI?solutions. Effective communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders. Key Responsibilities As an?AI/ML Solution Engineer, build AI/ML, Gen AI, Agentic AI empowered?practical in-depth solutions for solving customers business problems. As an?AI/ML Solution Engineer, design, develop, and deploy machine learning models and algorithms. Conduct research and stay up-to-date with the latest advancements in AI/ML, GenAI, and Agentic AI. Lead a team of junior AI engineers, providing direction and support. Skills: ml,learning,models,machine learning,skills,data,design,machine learning models,data science,etl,ai,sql,python,numpy,scikit-learn,pandas,gen ai,tensorflow,pytorch,ai framework,autogen,langgraph,crewai,agent force,llm Show more Show less

Greetings from BMW Techworks India Role: Mid-Level Generative AIEngineer Location: Bangalore or Chennai Experience: 7 to 10 Years Note: We are looking for 15 to 30 Days of Notice Period. What awaits you/ Job Profile: The BMW Group aims to harness the potential of generative AI across all business processes. By utilizing AI applications that assist business users in their daily tasks and creating autonomous AI agents capable of executing complex workflows, we envision a transformative AI-driven future. Central to this transformation is the BMW Group AI platform, GAIA (Group Artificial Intelligence Assistant), which offers a cutting-edge AI toolkit for developing applications and agents. The newly established AI Delivery Factory for GAIA will enhance this platform by integrating BMW-specific AI tools and agents, automating many manual tasks currently performed within our transactional IT systems. Your role will be pivotal in driving the BMW AI transformation. What should you bring along: 7+ years of experience in IT and 2 + in AI development Experience and deepen knowledge about Generative AI Knowledge about generative AI techniques and fine-tuning methods to improve model performance. Strong Python programming skills and experience with modern AI frameworks Familiar with implementing RAG (Retrieval-Augmented Generation) architecture for sophisticated AI applications Extensive knowledge of multimodal models, foundation models, and fine-tuning techniques. Expertise in designing and implementing scalable and efficient AI systems Excellent communication and collaboration skills, with the ability to lead and mentor junior team members Knowledge of software development processes in the automotive environment is advantageous Familiarity with cloud computing platforms and services for AI (AWS)

Job Title: Senior AI/ML Engineer Custom LLM & RAG Implementation Location: Hyderabad(WFO) Experience: 7+ years Notice: Immediate About the Role We are seeking a highly skilled and hands-on Senior AI/ML Engineer with strong expertise in building and deploying custom Large Language Models (LLMs) . The ideal candidate will have demonstrable experience in Retrieval-Augmented Generation (RAG) implementations, fine-tuning foundation models , and solving complex problems across domains using applied machine learning and natural language processing. This role is strategic and technical, requiring a blend of research, solution engineering, MLOps maturity, and domain adaptability. Key Responsibilities LLM Development & Deployment Design, build, and deploy customized LLM pipelines tailored to enterprise use cases. Implement end-to-end LLMOps workflows including model packaging, CI/CD, and monitoring. RAG & Fine-Tuning Implement RAG pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate) and document ingestion frameworks (e.g., LangChain, Haystack). Fine-tune open-source LLMs (e.g., LLaMA, Falcon, Mistral, MPT) on proprietary datasets using frameworks like Hugging Face Transformers and PEFT/LoRA. Solution Engineering Translate business problems into ML/LLM solutions with clear problem framing and data strategy . Collaborate with product, data engineering, and domain teams to prototype and deliver scalable solutions. Cross-Functional AI Applications Apply ML/LLM solutions across multiple verticals such as legal document analysis, customer support automation, compliance, supply chain optimization, or medical NLP. Build domain-agnostic prompt engineering strategies and apply zero-shot/few-shot learning where appropriate. Leadership & Mentorship Mentor junior engineers and contribute to AI/ML best practices . Act as a thought partner in innovation and experimentation within the team and with external stakeholders. Required Skills & Qualifications Bachelors or Masters in Computer Science, AI/ML, Data Science, or related field. 5+ years of hands-on experience in ML/NLP , with a recent focus on LLMs and foundation models. Hands on exposure in Transformers, RAG Implementation, LLM's PyTorch/TensorFlow, Lang Chain, OpenAI APIs, and popular model libraries. Experience deploying ML models to production using FastAPI, Docker, Kubernetes , or cloud-native tools (AWS/GCP/Azure). Familiarity with vector databases , embeddings, and search frameworks. Strong understanding of model evaluation metrics , bias/fairness in ML, and responsible AI practices. Ability to work cross-functionally with business, legal, and engineering teams. Preferred Qualifications Experience with RLHF (Reinforcement Learning from Human Feedback) . Published work in open-source communities or AI research conferences. Familiarity with multi-modal AI , autoML , or agentic workflows is a plus. Prior work in regulated domains (e.g., finance, healthcare, legal). Why Join Us Work on cutting-edge AI/LLM use cases that span industries and functions. Lead mission-critical AI initiatives from ideation to deployment. Be part of a collaborative, innovation-driven team shaping the next generation of enterprise AI solutions. Note: Interested candidates can share cv at sahithi.totharamudi@jteksoftware.in

We are hiring AL/ML Engineers with 5–8 years of experience in AI/ML, Agentic AI, Gen AI, TensorFlow, RAG pipelines, and LLM flows. Required Candidate profile Experienced AI/ML Engineer with expertise in Agentic AI, Gen AI, TensorFlow, RAG pipelines, and LLM workflows. Seeking challenging lead-level opportunities. Ready to join within 30 days.

Role Details: Position: AI Lead Location: Hyderabad, Telangana, India Key Responsibilities: Spearhead the end-to-end development, deployment, and continuous optimization of cutting-edge AI/ML systemsGenerative AI, LLMs/MLLMs, RAG, autonomous agents, and custom MCP servers in production Architect and implement scalable Retrieval-Augmented Generation pipelines, multi-modal transformer systems, and autonomous multi-agent frameworks (LangChain, AutoGPT, BabyAGI, NVIDIA NeMo Agents) Lead deep-learning model design and delivery: ANN, CNN, RNN, LSTM/BiLSTM, attention-based Transformers (BERT, GPT, T5, Vision Transformers), GANs, VAEs, Diffusion models, and Mixture-of-Experts architectures Define and enforce best practices for prompt engineering, fine-tuning (LlamaIndex, Hugging Face), quantization (INT4, GGUF), pruning, distillation, and advanced inference optimizations Build and maintain robust MLOps pipelines: CI/CD (Git, Bitbucket, automated tests), model versioning (MLflow, Hugging Face Hub & LFS), Docker/GPU containerization, Kubernetes/OpenShift orchestration, Terraform infrastructure as code Design high-performance data engineering workflows: ETL optimization (Pandas, NumPy, Spark), real-time streaming (Kafka, RabbitMQ), and caching strategies (Redis) Ensure secure, compliant AI deployments by embedding Responsible AI principles (bias mitigation, transparency, privacy), governance frameworks, and regulatory controls. Monitor emerging research (self-supervised pre-training, federated learning, synthetic data, LLMOps) and integrate top innovations into production Collaborate closely with Product, DevOps, Data Engineering, and Security teams; mentor and guide engineers and data scientists in software engineering and model validation best practices Required Qualifications: Education: Masters or PhD in AI/ML, Computer Science (AI/ML specialization), Data Science, Mathematics, or related field Industry Experience: 15+ years in AI/ML roles, including 710 years hands-on in Generative AI and Deep Learning, plus 5+ years in senior or leadership positions Hands-On Coding & Deployment: Expert at architecting, writing, debugging, deploying, and optimizing production-grade AI/ML code in Python (primary), C++, R, Java/Spring Boot, with strong testing, code-review, and performance-profiling discipline Deep Learning & Generative AI Frameworks: Advanced usage of PyTorch, TensorFlow, ONNX, GGUF, Hugging Face Transformers & Diffusers; fine-tuning pipelines (LlamaIndex, custom scripts) Large Language & Multimodal Models: Production deployment of LLMs, Multimodal LLMs (vision-language models, cross-modal understanding), RAG systems, and custom MCP A2A servers; embedding management & vector search with Pinecone, Milvus, Chroma, Quadrant Advanced Model Optimization: Quantization, pruning, distillation, MoE routing, efficient inference strategies, prompt-engineering platforms (LangSmith, PromptFlow) Classical & Advanced ML: Proficiency in regression, decision trees, random forests, SVM; boosting (XGBoost, CatBoost, LightGBM); clustering (K-Means, DBSCAN, hierarchical); RL (Q-Learning, DDPG, PPO); statistical methods and optimization math Computer Vision & Document Processing: Expertise in OpenCV, PyMuPDF, python-docx/pptx, pytesseract for advanced text/image extraction and analysis Cloud & Infrastructure: GPU acceleration (CUDA, cuDNN); AWS (Bedrock, SageMaker), Azure AI Studio & GPU Containers, GCP (Vertex AI, Cloud Run), serverless AI, NVIDIA Triton Inference Server Backend & APIs: FastAPI, OpenAPI, Django REST Framework, Flask for building and scaling AI microservices Data Engineering & Storage: ETL pipelines, streaming, caching; relational (MySQL, Oracle SQL), NoSQL (MongoDB), vector DBs MLOps & Observability: MLflow, Kubeflow; Docker, Kubernetes, OpenShift; CI/CD (Git, Bitbucket); monitoring with Prometheus, Grafana, OpenTelemetry, Logstash, Kibana Security & Compliance: Secure coding, network security, and adherence to GDPR, HIPAA, GxP standards Industry Certifications & Research: Must hold at least one recognized AI/ML certification (e.g. AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate) and have published research papers in top-tier AI/ML conferences or journals (NeurIPS, ACM, arXiv, AAAI, JMLR). Good to Have Skills: PhD-level publications and advanced certifications (Stanford AI, MIT, AWS, Google) Experience with federated learning, synthetic data generation, privacy-preserving ML (differential privacy, homomorphic encryption), and edge/in-device inference (TensorFlow Lite, CoreML) Familiarity with Responsible AI toolkits, model cards/DataCard’s, and AI risk management frameworks Significant open-source contributions to major AI/ML projects Proven success integrating AI in regulated industries (Texting/Messaging, pharma, healthcare, finance) Industries and disciplines. How to Apply: If you are a passionate developer who loves coding and thrives in an innovative startup environment, apply now to join our journey in revolutionizing communication! Apply here or email to join@beetexting.com

Role & responsibilities Experimenting with new Generative AI models Developing proof of concepts and pilots for various Generative AI and Agentic AI use cases Collaborating with Solution Architects and Enterprise Architects Evangelizing Generative AI and AI adoption within the bank Creating and presenting demos to promote reference architectures Experience: 5+ years of relevant experience Skills: 1. Programming Languages: a. Python 2. Machine Learning Frameworks: a. PyTorch b. TensorFlow 3. Experience with Generative AI Models: a. GANs (Generative Adversarial Networks) b. VAEs (Variational Autoencoders) c. Transformers 4. Cloud Platforms: a. AWS (Amazon Web Services) b. GCP (Google Cloud Platform) c. Azure 5. Data Handling: a. Feature stores b. Vector stores c. Retrieval-Augmented Generation (RAG) d. Data visualization 6. Big Data Technologies: a. Spark 7. Workflow Orchestration: a. Airflow

AI/ML Development Leadership: Lead the implementation of machine learning models and automation pipelines for CPT/ICD code prediction and claims processing. Develop and optimize retrieval-augmented generation (RAG) workflows using LLMs, vector databases (e.g., FAISS), and custom prompts. Direct the design of structured training datasets derived from SOAP notes, payer files, and denial records. Team & Project Management: Manage day-to-day activities of India-based engineers and coding specialists. Coordinate closely with U.S.-based consultants to ensure AI solutions align with reimbursement policy and documentation standards. Track project milestones, guide model improvements, and ensure output quality. Technical Execution: Build, fine-tune, and deploy models using PyTorch, TensorFlow, HuggingFace Transformers , and scikit-learn . Integrate LLM APIs for code summarization and document understanding. Implement vector search and orchestration platforms for real-time AI assistance. Role & responsibilities Preferred candidate profile

Job Title: AI Engineer Location: Chennai Experience: 2-4 years Employment Type: Full-Time Job Summary: We are seeking an AI Engineer with strong proficiency in Python and hands-on experience in building AI-powered applications. The ideal candidate should have experience working with FastAPI, Langchain, and Pydantic, along with a solid understanding of Generative AI concepts, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG). Key Responsibilities: Develop, integrate, and optimize AI-powered applications using FastAPI and Langchain. Design and deploy APIs using FastAPI with Pydantic for data validation. Implement and fine-tune solutions leveraging Large Language Models (LLMs). Build and optimize Prompt Engineering pipelines for LLM interactions. Design and implement Retrieval-Augmented Generation (RAG) solutions for enhanced contextual responses. Collaborate with data scientists, product managers, and engineers to deliver high-quality AI applications. Continuously research and experiment with advancements in Generative AI technologies. Key Skills & Technologies: Programming: Python (Intermediate to Advanced) Frameworks & Libraries: FastAPI (API development) Langchain (LLM integrations & workflows) Pydantic (Data validation and settings management) AI/ML Concepts: Generative AI (Basics) Large Language Models (LLM) Understanding architecture, capabilities, and limitations Prompt Engineering – Techniques for effective LLM interactions Retrieval-Augmented Generation (RAG) – Building hybrid retrieval-generation systems Version Control: Git, GitHub/GitLab CI/CD: Familiarity with deployment pipelines (optional) Preferred/Optional (Good to Have): Experience with AI Agent Frameworks such as: LangGraph CrewAI Knowledge of Vector Databases (e.g., FAISS, Chroma) Cloud Platforms (AWS, Azure, GCP) Containerization (Docker)

Design and fine-tune AI apps using GPT, BERT, Azure OpenAI, and Cognitive Services. Build chatbots with Copilot Studio, RAG pipelines, vector DBs, Graph API, and M365 Plugins. Code in Python/Node.js with REST API integration. Required Candidate profile 5+ years of experience in AI/ML or Conversational AI Strong grip on prompt engineering and model fine-tuning Deep understanding of Microsoft’s AI ecosystem

Responsibilities: * Lead ML projects from ideation to deployment using Microsoft tools. * Collaborate with cross-functional teams on project requirements and deliverables. Work from home