689 Langchain Jobs - Page 14

As a Staff Data Scientist at PhysicsWallah (PW), you will play a pivotal role in driving innovation in Generative AI and advanced Machine Learning (ML) to enhance personalized and scalable learning outcomes for students across Bharat. With your expertise and experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Reinforcement Learning, and model fine-tuning, you will lead the design and development of cutting-edge AI solutions that power intelligent content generation, adaptive learning, and personalized experiences for millions of learners. Your responsibilities will include collaborating with cross-functional teams to create next-gen AI solutions using LLMs, RAG, and RL techniques. You will fine-tune and customize models for PW-specific education use cases, architect scalable pipelines for model training and deployment, integrate models into real-world applications, conduct rigorous experimentation and testing to enhance model performance, and stay updated with the latest trends in AI frameworks and research. To excel in this role, you will need a minimum of 8 years of hands-on experience in Data Science/ML, with a recent focus on GenAI, LLMs, and deep learning. Proficiency in RAG architectures, transformer-based models, Reinforcement Learning, Python, ML frameworks such as PyTorch and TensorFlow, cloud platforms like AWS/GCP, and MLOps for scalable AI model deployment is essential. Your track record of shipping ML models into production environments, strong communication skills, and ability to work in cross-functional settings will be crucial. If you have published papers, patents, or contributions to open-source GenAI projects, experience in edtech or adaptive learning platforms, exposure to vector databases and semantic search systems, and are driven by a passion to make quality education accessible to all, then joining PW will provide you with an opportunity to work on cutting-edge GenAI problems with a large-scale real-world impact in a collaborative and fast-paced environment that offers immense learning opportunities. Shape the future of education with GenAI at PhysicsWallah by applying now and contributing to our mission of democratizing learning and transforming the way students access affordable, high-quality education.,

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.,

The position of AI & Data Intern at Novasensa in Delhi NCR is a valuable opportunity to contribute to the development of a custom AI Assistant aimed at automating experiments, analyzing lab data, and supporting decision-making in sustainability challenges. As an intern, you will work with the R&D team to shape this tool and apply your programming skills to real-world scenarios. This internship offers a chance to use Python and data skills on an AI system, learn about AI's role in clean-tech innovation, and gain mentorship from a startup team working at the intersection of sustainability, engineering, and software. Your responsibilities as an AI & Data Intern will include supporting the development and testing of internal AI tools, such as programming and automation tasks. You will write Python scripts for data processing, automate R&D tasks, and assist in building backend tools for experiment tracking and analysis. Additionally, you will be involved in data analysis and visualization, where you will analyze lab results, generate visual summaries, and track patterns and insights from recycling experiments. Furthermore, you will contribute to AI Assistant Development by helping with document parsing, semantic search, and improving the performance of the AI assistant using real lab data. The ideal candidate for this internship is a curious and motivated learner with basic to intermediate Python programming skills, an understanding of data structures and functions, familiarity with data visualization tools, and an interest in AI and sustainability. Exposure to AI tools and experience with data cleaning and automation are considered advantageous. Candidates pursuing or holding degrees in Computer Science, Data Science, AI, ML, Statistics, Mathematics, or related fields are encouraged to apply. Past interns have highlighted Novasensa as a unique opportunity to work on deep-tech projects with a real impact on sustainability. If you are passionate about using your coding skills to contribute to a cleaner planet, this internship at Novasensa is the perfect opportunity for you. To apply, send your resume along with a short note explaining why you want to intern at Novasensa and what you hope to learn and contribute to hr@novasensa.com. Early applications are preferred as they are reviewed on a rolling basis. Join Novasensa to learn, build, and make an impact with your code for a greener future.,

You will be responsible for building curated enterprise-grade solutions for GenAI application deployment at a production scale for clients. Your role will involve a solid understanding and hands-on skills for GenAI application deployment, which includes development and engineering tasks. This will include data ingestion, selecting suitable LLMs, implementing simple and advanced RAG, setting up guardrails, prompt engineering for optimization, ensuring traceability and security, evaluating LLMs, enabling observability, and deploying at scale on the cloud or on-premise. It is crucial that candidates also showcase knowledge on agentic AI frameworks, with a preference for those having a strong background in ML with engineering skills for the LLMOps role. The ideal candidate should possess 3 - 5 years of experience in working on ML projects, encompassing tasks such as business requirement gathering, model development, training, deployment at scale, and monitoring model performance for production use cases. Proficiency in Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, and optionally AgentOps is essential. Prior experience working with both proprietary and open-source large language models, fine-tuning LLMs, creating distilled models from hosted LLMs, building data pipelines for model training, and tuning model performance, RAG, guardrails, prompt engineering, evaluation, and observability is required. Moreover, candidates should have experience in GenAI application deployment on cloud and on-premises at scale for production, creating CI/CD pipelines, working with Kubernetes, deploying AI services on at least one cloud platform (AWS/GCP/Azure), creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGen, and optionally developing lightweight UI using streamlit or chainlit. Desired experience with open-source tools for ML development, deployment, observability, and integration, as well as a background in DevOps and MLOps, will be advantageous. Proficiency in collaborative code versioning tools such as GitHub/GitLab, along with strong communication and presentation skills, is essential. A B.E/B.Tech/M.Tech in Computer Science or a related technical degree or equivalent qualification is required. If you are someone who enjoys challenging growth opportunities and thrives in a dynamic environment working alongside enthusiastic over-achievers, this role might be the perfect fit for you.,

We are seeking a Mid-Level LLM Application Developer with 3+ years of experience in software development, who is enthusiastic about constructing intelligent applications utilizing Azure OpenAI, Python, and LLM frameworks. This full-time position is dedicated to the design, development, and implementation of scalable LLM-powered solutions, such as chatbots, knowledge assistants, and RAG-based systems. You will collaborate closely with cross-functional teams to materialize innovative AI solutions, capitalizing on the latest generative AI and agentic technologies. Responsibilities: - Design and develop LLM-powered applications utilizing Python and Azure OpenAI services. - Construct end-to-end Retrieval-Augmented Generation (RAG) pipelines, incorporating vector databases, semantic search, and related tools. - Develop conversational agents and virtual assistants, employing frameworks like LangChain or LlamaIndex. - Create effective prompts using advanced prompt engineering and design techniques. - Integrate LLMs with external tools, APIs, and business data systems. - Apply Agentic AI patterns to RAG and AI Workflows, engaging with LLMs by orchestrating various agents together. - Deploy and manage applications using Azure Functions, Azure AI services, and serverless components. - Ensure performance, scalability, and reliability of AI solutions on Azure. - Collaborate across teams and participate in agile development processes. Required Skills (Must Have): - Proficiency in Python programming language. - Expertise in Azure OpenAI Service, including foundation model usage and integration. - Build and deploy AI solutions leveraging Azure AI services (e.g., Cognitive Services, Azure ML, Azure AI Search). - Deep experience in prompt engineering, including various prompting strategies (few-shot, chain-of-thought, etc.). - Hands-on experience building RAG pipelines with vector databases and tool integrations. - Proven experience developing chatbots or virtual assistants using LLMs. - Proficiency in at least one LLM application framework (e.g., LangChain, LlamaIndex). - In-depth understanding of LLM models, their capabilities, and applications. - Good understanding of LLM evaluations, and how to evaluate LLM model outputs. - Good understanding of using AI Agents and Agentic AI Patterns to integrate with LLMs. - Experience deploying with Azure Function Apps and broader Azure ecosystem. - Solid grasp of API integrations and data workflow design. - Strong problem-solving skills and ability to deliver scalable, efficient code. - Excellent communication and team collaboration abilities. Preferred Skills (Good to Have): - Familiarity with Multi-Agent AI orchestration and agentic workflows. - Experience building cloud-native services with serverless architectures. - Understanding of NLP techniques and data transformation pipelines. - Familiarity with LLMOps concepts and AI model lifecycle. Qualifications: - Bachelor's degree in computer science, Computer Engineering, or a related field. - 3+ years of experience in software development. - Experience with LLM applications and cloud platforms. - Strong understanding of software development methodologies (e.g., Agile). Location: DGS India - Pune - Kharadi EON Free Zone Brand: Dentsu Creative Time Type: Full time Contract Type: Permanent,

Position Lead Data Scientist JD Good understanding of GenAI LLM models (ChatGPT, LLAMA 2, etc.), Vector databases, LangChain, and LlamaIndex. Hands-on experience with Deep Learning architecture, NLP, and OCR. Expertise in deep learning frameworks such as TensorFlow, PyTorch, and Keras. Experience with Generative AI models like GANs, VAEs, and transformers. Knowledge of Agentic AI concepts and applications. Proficiency in data preprocessing, feature engineering, and model evaluation. Experience with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models. Python Fast API experience, SDA based implementations for all the APIs. Good understanding of Prompt Engineering Deep Learning Frameworks:TensorFlow, PyTorch, Keras Generative AI Models:GANs, VAEs, Transformers Agentic AI Tools:OpenAI Gym, Unity ML-Agents Natural Language Processing Libraries:NLTK, SpaCy, Hugging Face Transformers Computer Vision Libraries:OpenCV, TensorFlow, PyTorch Total Experience 7-11 Yrs Relevant Experience 6+years Any Preferred Skills Must have Skills GenAI LLM models (ChatGPT, LLAMA 2, etc.), Vector databases, LangChain, and LlamaIndex. Role (Development/Support) Development Shift (General/Rotational) Timings General Max Budget 30 LPA Location Mumbai, Pune, Chennai, Noida, Bangalore Office Mode Hybrid

About the Role: We are looking for a highly skilled and motivated Data Scientist with 35 years of experience to join our Data Innovation team. The ideal candidate will have strong analytical skills, hands-on experience in Computer Vision and Large Language Models (LLMs), and a proven track record of turning complex data into actionable insights and intelligent solutions. This role will involve working on high-impact AI solutions for unstructured data, including images and documents. Designation – Data Scientist Key Responsibilities: Design, develop, and deploy models for computer vision tasks such as object detection, image classification, OCR, segmentation, etc. Build and fine-tune LLM-based pipelines for tasks such as information extraction, document summarization, chat-based interfaces, and automated reasoning. Work closely with cross-functional teams (engineering, product, business) to translate business problems into data science solutions. Conduct exploratory data analysis, statistical modelling, and feature engineering across diverse data sources. Evaluate model performance using appropriate metrics and iterate for improvement. Stay up to date with the latest research and advancements in AI/ML, computer vision, and NLP. Required Qualifications: Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related fields. 3–5 years of hands-on experience in Data Science or Machine Learning roles. Strong proficiency in Python and ML libraries such as scikit-learn, pandas, PyTorch/TensorFlow, OpenCV, Langchain etc. Experience with Computer Vision frameworks (e.g., YOLO, Detectron2, MM Detection) and LLMs (e.g., Hugging Face Transformers, Lang Chain, LLaMA, GPT). Experience with real-world model deployment and evaluation. Strong grasp of machine learning concepts, statistical analysis, and data manipulation. Excellent problem-solving, communication, and stakeholder collaboration skills. Good to have: Exposure to the lending, finance, or banking domain (e.g., credit scoring, income estimation, fraud detection). Experience with document AI or multi-modal AI systems. Familiarity with cloud platforms (AWS/GCP/Azure) and MLops tools. Experience working with OCR engines (Tesseract, PaddleOCR, etc.) and integrating CV+LLM pipelines. Understanding of RAG pipelines, fine-tuning of open-source LLMs, or prompt engineering. Location – Ahmedabad (Onsite) Experience – 3 to 5 Years

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.

Must have Strong proficiency in Python with the ability to write clean, modular, and efficient code for AI/ML workflows and backend services. Hands-on experience building AI agents and pipelines using LangChain and LangGraph to orchestrate LLM-based reasoning, tool usage, and decision making. Familiarity with using, fine-tuning, and evaluating popular foundation models (e.g., OpenAI, Claude, Mistral, LLaMA) for text generation, classification, and summarisation tasks. Practical experience with vector databases like Pinecone, QDrant, Weaviate, or FAISS for semantic search, retrieval-augmented generation (RAG), and embedding management. Proficiency with IaC tools such as Terraform, AWS CloudFormation, or Pulumi to automate infrastructure provisioning and deployment in cloud environments. Strong understanding of cloud-native architecture patterns and experience deploying AI workloads on AWS services such as Lambda, ECS, S3, and SageMaker. Experience designing and consuming RESTful APIs and integrating AI models into applications via APIs (e.g., OpenAI, Bedrock, Hugging Face). Knowledge of prompt design, few-shot learning, prompt templates, and optionally, fine-tuning or adapters like LoRA. Exposure to modern DevOps practices, containerisation (Docker), and CI/CD pipelines for deploying ML/AI systems. Strong analytical mindset, ability to work independently, and collaborate across teams including data scientists, engineers, and product managers. Req 2 - Good to have Experience with deep learning frameworks like PyTorch or TensorFlow to build and train custom AI/ML models. Familiarity with ML model tracking tools such as MLflow or SageMaker Experiments for managing experiments and monitoring model performance. Understanding of model deployment at scale, including real-time inference using tools like SageMaker, TorchServe, or ONNX. Exposure to MLOps practices, including pipeline automation, model versioning, and integration with CI/CD tools for seamless deployment and monitoring.

Role & responsibilities Design and deploy scalable AI solutions using Azure AI services Write and integrate Python code for AI models, data ingestion and automation. Work with senior developers and cross-functional teams to implement AI features into current systems and applications. Stay updated with the latest advancements in AI and Azure technologies. Preferred candidate profile Bachelors degree in computer science, Engineering, or a related field. Proficiency in programming languages such as Python or C# 5+ years of experience with AI solutions using Azure AI services Experience with LangChain or Semantic Kernel frameworks Experience with Azure AI Services like AI Search, OpenAI and Document Intelligence Experience with Azure Compute Services such as Azure Functions and Apps Services Experience with API development and integration Strong problem-solving skills and attention to detail

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 10+ years. Expertise in Python, LLM integration, and GenAI development workflows Strong knowledge of prompt engineering, vector databases, retrieval-augmented generation (RAG), and toolchains Strong working experience in Agentic AI and Open AI. Hands-on experience with agent frameworks like LangChain Agents, Semantic Kernel, Haystack, or custom-built agents Proven experience in leading LLM/GenAI projects from Proof-of-Concept to Production Deep understanding of modern data workflows ingestion, transformation, cataloguing, validation, and analytics Ability to work collaboratively across engineering, product, and governance teams Experience with enterprise data products, MLOps, or DataOps platforms Familiarity with governance workflows and metadata-driven automation Exposure to cognitive architectures or agent simulation environments Excellent communication and collaboration skills. RESPONSIBILITIES: Understanding the client’s business use cases and technical requirements and be able to convert them into 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 client’s 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.

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/TbiZ5o9oN2ZtJSpKA 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

We are looking for a passionate and innovative AI/ML Engineer LLM & NLP with strong expertise in artificial intelligence, natural language processing (NLP), and large language models (LLMs). The focus is on crafting, optimizing, and scaling AI-driven interactions that improve system performance, enhance user experience, and deliver measurable business value across a variety of applications. Key Responsibilities: Design, test, and refine prompts to optimize performance of LLMs such as GPT-4, Claude, Gemini, and open-source models. Collaborate with cross-functional teams (product, design, engineering, marketing) to develop AI-driven features and tools. Conduct experiments and evaluate to test the accuracy, safety, and quality of AI-generated outputs, learning best practices along the way. Automate prompt workflows and integrate prompt chains with APIs and tool stacks. Fine-tune models or build retrieval-augmented generation (RAG) pipelines when needed. Stay curious and keep learning about the latest advancements in generative AI, NLP, and prompt engineering through hands-on practice and research Contribute to building internal documentation, prompt templates and reusable libraries. Required Skills & Qualifications: Bachelors degree in computer science. 2 years of experience working with LLMs, AI systems, NLP frameworks. Strong understanding of transformer models and training. Experience using OpenAI (ChatGPT, GPT API), Anthropic, Cohere, Hugging Face, or similar platforms. Strong proficiency in Python, with hands-on experience using leading AI frameworks and libraries such as LangChain, LlamaIndex, and others commonly used in LLM and NLP development. Background in UX, technical writing, or content design is a plus.

Aptean is seeking an Associate Architect, AI to join our innovative team. In this pivotal role, you will be instrumental in designing, developing, and refining AI solutions, with a strong focus on optimizing AI model output through advanced prompting techniques. You'll work with cutting-edge technologies like Azure OpenAI and Microsoft Fabric Lakehouse to build scalable, efficient, and business-aligned AI applications, including autonomous AI agents and enhanced conversational AI experiences. About the Role Develop and refine structured prompts to optimize AI model output, experimenting with various prompting techniques. Implement Fabric AI Skills on Fabric Lakehouse for automated data interpretation of semantic models for improved contextual accuracy. Integrate Azure OpenAI and Fabric AI Skills for the MS Fabric Lakehouse to enable enhanced conversational AI experiences. Drive the development of AI-led automation solutions , preferably leveraging Agentic AI. Analyze AI responses, troubleshoot inconsistencies, and fine-tune prompts for better accuracy while researching and implementing best practices to reduce hallucinations and biases . Automate workflows by designing prompts for AI agents, chatbots, and AI-powered assistants. Stay updated with advancements in NLP, LLMs, and generative AI to continuously improve prompt strategies and enhance AI model performance. Assist in curating, cleaning, and processing datasets used for training machine learning models. Learn to create effective prompts for LLMs to generate and augment datasets while helping identify and resolve data quality issues across various data types. Develop and implement AI models, algorithms, and workflows to automate tasks, optimize processes, and generate insights from data. Drive research and implementation of autonomous AI agents that interact with users, applications, and environments. Optimize AI performance, ensuring solutions are scalable, efficient, and aligned with business objectives . Skills, Abilities & Competencies Experience working with LLMs (GPT, Claude, Gemini, Llama, etc.) and AI APIs . Hands-on experience in Fabric AI Skills and implementing Fabric AI Skills on Fabric Lakehouse. Familiarity with Data Lakehouse & medallion architecture , including semantic models. Familiarity with Python, OpenAI API, LangChain, and AI automation frameworks . Proficient with Python language and ML toolkits like TensorFlow, PyTorch, Keras, Scikit Learn . Strong programming skills in languages such as JSON, Microsoft Azure, Python, Java, JavaScript , etc. Prior experience developing and hosting chatbots on multiple channels (Teams, SharePoint, web portal). Understanding of statistical models such as regression, clustering, and ML algorithms such as decision trees, Random Forests, neural networks, etc. Strong understanding of NLP principles, model behavior, and prompt design techniques . Ability to interpret AI-generated outputs and optimize performance. Strong writing and communication skills, with a keen understanding of AI-driven content generation. Adaptability to a fast-paced AI startup environment. Qualifications Education: Bachelor's degree (Required). Master's degree (Preferred). Work Experience: 8-12 years of relevant experience.

About the Role We are hiring a Product Growth Manager to lead initiatives at the intersection of retail, AI, and product execution. This role requires someone who can conceptualize and build AI-native features, scale them effectively, and drive adoption through experimentation, data insights, and structured execution. You will work closely with engineering, machine learning, product, and business teams to deliver AI-powered capabilities that solve real-world retail challenges. The ideal candidate has strong technical foundations, sharp product instincts, and a proven ability to operate with speed and ownership in high-growth environments. What will you do at Fynd Build and launch AI-native product features in collaboration with ML and engineering teams. Drive product-led growth initiatives focused on activation, retention, and adoption. Translate AI/ML capabilities into scalable and intuitive product experiences. Work hands-on with model deployments, inference systems, and API integrations. Own end-to-end product executionfrom problem discovery to roadmap delivery and post-launch iteration. Contribute to platform strategies that scale AI features from MVPs to production-grade adoption. Understand and influence product flows specific to retail, catalog systems, and commerce automation. Some Specific Requirements: AI and Technical Foundations Strong grasp of LLMs, embeddings, vector databases, RAG, and fine-tuning methods like LoRA and QLoRA. Hands-on experience with OpenAI, Hugging Face, LangChain, LlamaIndex, and production-grade AI tooling. Familiar with AI workflows using FastAPI, Docker, MLflow, and model serving via Ray or TorchServe. Comfortable working with GitHub, Git, and tools for managing models, code, and experiments. Good understanding of microservices, API design (REST/GraphQL), and scalable backend systems. Experienced in CI/CD setup for training and deploying ML models to production. Data and Analytics Proficient in SQL, BigQuery, and Looker Studio for data exploration and dashboards. Able to design KPIs, success metrics, and user journey insights for product analytics. Knowledge of tools like dbt, Airflow, and event-based platforms like PostHog or Mixpanel. Experience with A/B testing, funnel analysis, and behavioral cohort tracking. Retail and Product Execution Solid understanding of retail workflows, product catalogs, and commerce ecosystems. Experience building and scaling digital products with real-world user adoption. Strong product judgment and ability to balance business, user, and technical priorities. Stakeholder Management and Execution Leadership Ability to lead and influence cross-functional teams to drive high-quality execution. Strong communication skills to present AI-driven concepts to both technical and non-technical audiences. Experience with Agile methodologies and tools such as Jira, Confluence, and Asana for planning and tracking. Preferred Experience 2 to 5 years in product, growth, or AI-focused roles. Experience in building and scaling AI-powered or technology-driven platforms. Exposure to retail, e-commerce, or SaaS environments. Track record of delivering outcomes in fast-paced, cross-functional teams. Why Join Us Be part of a team shaping the future of AI-native platforms in digital commerce. Work closely with leading AI engineers, product teams, and business stakeholders. Own and execute high-impact initiatives with autonomy and accountability. Operate in a culture that values speed, clarity, and innovation. If you're someone who thrives on execution, loves solving complex problems, and wants to build the future of AI-native platforms, we'd love to have you on board

Our team is a part of Oracle CSS who solutions, designs and develops AI applications for Managed Customer requirements. You'll join a team of talented, driven, and diverse individuals, each bringing unique perspectives and expertise. Our team develops cutting-edge applications across both AI and non-AI domains. Your expertise will be pivotal in building end to end software solutions flows that include Architecture design, database design, conversational AI solutions, Agentic flows using LLM and other cutting-edge Machine learning techniques. In this role, you will design, develop, and build scalable services using agile methods leveraging the latest and greatest advancements in software development and AI to solve complex business problems intelligently. Responsibilities Translate business needs into advanced machine learning AI services and provide strong algorithm and coding execution and delivery of Machine Learning & Artificial Intelligence. Build high-quality, scalable, and efficient software solutions that brings GenAI capabilities, leveraging latest advancements such as Agentic LLM and RAG frameworks, etc. Leverage Agentic AI (Autogen, Langchain, etc.) and in-house ML tools & OCI platform to develop reusable, highly performant machine learning systems. Lead architectural discussions and provide technical guidance to ensure the adoption of best practices and alignment with the overall technology roadmap. Work closely with product owners/managers to understand requirements, translate them into technical specifications, and deliver features in a timely manner. Participate in code reviews, providing constructive feedback and ensuring code quality and adherence to coding standards. Work with peers to propose and review design, solutions and implementation with an emphasis on metric driven results. Preferred Skills and Experience Experience with AI/ML frameworks and libraries is a significant asset. Experience working in Generative AI, Customizing LLM's, is an added advantage. Experience in Agentic AI. Autogen, LangGraph, etc. Experience in OJET. Experience with build automation, continuous integration, or continuous deployment tools such as Git, Jenkins, Ansible, etc. Experience in developing and designing solutions with containerization technologies such as Docker and Kubernetes. Experience with cloud observability tools and practices. Minimum Qualifications 8+ years of full-stack software development experience. 1+ year of experience with software design and architecture. Bachelor's or master's in computer science, Engineering, or a related field. Experience in Python and Fast API. REST API - Client and API service development. Experience in cloud technologies - OCI, GCP, AWS etc. OCI is preferred. Good grasp of cloud development concepts like micro-services, BFF, distributed storage. Experience with JavaScript UI development with frameworks like React. Proficient in working with both SQL (e.g.: Oracle, PostgreSQL) and NoSQL databases (e.g., MongoDB, Redis) Experience driving architecture / design reviews, documentation. Experience in complete life cycle of software development including development, testing, installation, configuration, and deployment. Possess excellent verbal and written skills. Career Level - IC4

At CredArtha, we are revolutionizing financial intelligence with FINA (Financial Intelligence & Neural Analyst), our proprietary vertical LLM designed to process, analyze, and generate financial insights. Our mission is to empower financial institutions, businesses, and individuals with AI-driven precision, efficiency, and automation in financial decision-making. We are looking for a Senior Machine Learning Engineer who is passionate about LLMs, deep learning, and NLP and is eager to build cutting-edge AI models tailored for financial data processing, document understanding, and predictive analytics. If you have expertise in training and fine-tuning open-source LLMs, developing retrieval-augmented generation (RAG) systems, and optimizing NLP models for real-world applications, we want you on our team. Your Role & Responsibilities As a Senior Machine Learning Engineer, you will: LLM Development & Optimization - Design, train, and fine-tune FINA, leveraging open-source LLMs such as LLaMA, Falcon, Mistral, and GPT-J for financial applications. - Implement parameter-efficient fine-tuning (PEFT) techniques to optimize model efficiency while maintaining accuracy. - Work on self-learning mechanisms to ensure FINA continuously evolves through user interactions and real-time financial data ingestion. NLP & Financial Data Processing - Develop and enhance NLP models for document understanding, financial risk analysis, and transaction categorization. - Work on named entity recognition (NER), sentiment analysis, topic modeling, and automated financial report generation. - Design embedding models and vector search architectures to create a robust financial knowledge base. RAG & AI-Powered Financial Insights - Implement retrieval-augmented generation (RAG) pipelines to enhance LLM response accuracy and domain knowledge. - Build custom search and retrieval mechanisms using vector databases like FAISS, Weaviate, or ChromaDB. - Develop multi-modal AI models that combine structured and unstructured financial data to provide deep insights and analytics. Deployment, MLOps & Scalability - Deploy and manage FINA using cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and MLOps best practices. - Optimize models for low-latency inference and scalability using quantization, distillation, and model pruning techniques. - Implement real-time monitoring and feedback loops to improve model performance and user experience. Ideal Candidate Profile We are looking for someone who has: - Hands-on experience in Machine Learning, Deep Learning, and NLP (LLMs, Transformers, RNNs, etc.). - Strong proficiency in Python, with experience in TensorFlow, PyTorch, Hugging Face Transformers, and LangChain. - Expertise in fine-tuning LLMs, self-supervised learning, and AI explainability. - Experience working with financial data (bank statements, credit reports, transactional data, risk models, etc.). - Strong knowledge of vector embeddings, search algorithms, and RAG implementations. - Familiarity with database technologies (SQL, MongoDB, NoSQL) and cloud platforms (AWS, GCP, Azure). Bonus: Experience in financial risk modeling, fraud detection, or credit scoring models. Why Join CredArtha - Innovate at the intersection of AI & Finance - Work on groundbreaking AI-driven financial solutions. - Build FINA from the ground up - Develop a vertical LLM that will be at the core of CredArtha's technology stack. - Impact millions - Help businesses and financial institutions automate, analyze, and optimize decision-making with AI. - Freedom to experiment - Push the boundaries of deep learning and NLP in a fast-paced, innovation-driven environment.,

As an AI/ML Developer at our innovative organization, you will have the exciting opportunity to work on AI initiatives and contribute to the development of innovative solutions. Your key responsibilities will include developing and maintaining applications for AI and LLM projects, conducting data analysis to identify trends and insights for model improvement, designing, developing, and deploying machine learning models for various applications, optimizing algorithms for performance and scalability, and staying up-to-date with the latest advancements in AI. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science or a related field from a recognized university, with internship experience in AI or related fields being preferred. You should also have demonstrable experience in AI/ML programming and development, proficiency in working with OpenAI technologies and Vector Databases, experience with Large Language Models (LLMs), strong knowledge of LangChain, LLamaIndex, or any other framework, experience with API development and relational databases, excellent problem-solving skills, attention to detail, and the ability to work independently and in a team environment. Join us on this exciting journey to advance AI technology and utilize your skills in machine learning model development, LLM Index, vector databases, algorithm optimization, data analysis, OpenAI technologies, artificial intelligence, API development, large language models (LLMs), AI/ML programming, and relational databases to make a significant impact in the field of AI.,

As an AI Engineer, you will play a crucial role in our innovative startup that is dedicated to utilizing Artificial Intelligence to create transformative solutions. You will be responsible for designing, developing, and implementing AI applications, with a particular focus on Large Language Models (LLMs) and agentic frameworks. Collaborating closely with cross-functional teams, you will contribute to building robust AI solutions that leverage various models and inference points. Your key responsibilities will include designing and developing applications using LLMs and agentic frameworks to address real-world problems, setting up inference points to optimize AI model performance, and integrating AI capabilities into existing products and services in collaboration with software engineers and data scientists. You will utilize technologies like Autogen, LangChain, and AWS Bedrock to build and deploy AI solutions, and contribute to the development of generative AI applications that enhance user experiences and drive innovation. It is essential to stay updated with the latest advancements in AI and machine learning to continuously enhance our technology stack. To qualify for this role, you should have 2-3 years of experience in AI engineering or a related field, emphasizing LLMs and generative AI. Proficiency in agentic frameworks and designing applications around them is necessary, along with expertise in utilizing tools and technologies such as Autogen, LangChain, and AWS Bedrock. Strong programming skills in languages commonly used in AI development, like Python and Java, are required, as well as experience with multiple AI models and their inference setups. Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment are also highly valued. If you are passionate about pushing the boundaries of technology and creating impactful AI solutions, this opportunity with our hiring partner is ideal for you. Join us at our startup, where we are committed to leveraging AI to drive innovation and provide unparalleled growth opportunities for talented individuals in the dynamic landscape of Tech Jobs.,

We are seeking a Senior Python Backend Developer to join our team and take charge of building REST APIs and serverless functions in Azure using Python. As a Senior Python Backend Developer, your main responsibility will be developing high-performance and responsive REST APIs to cater to front-end requests. It will be essential for you to collaborate with team members working on various layers of the application and integrate front-end elements provided by co-workers. Therefore, having a basic understanding of front-end technologies is crucial for this role. Your duties will include delivering top-quality working software independently, writing secure and efficient code, and designing low-latency, high-availability applications. You will also be tasked with integrating user-facing elements developed by front-end developers, implementing security measures, and ensuring data protection. Additionally, your role will involve working with various Azure services like Azure Functions, APIM, Azure storage, SQL, and NoSQL databases, as well as writing automated tests and integrating with Azure APIM, Tracing, and Monitoring services. To excel in this role, you should have experience in building Azure Functions with Python, be proficient in Python with knowledge of at least one Python web framework, and have familiarity with ORM libraries. You should also be capable of integrating multiple data sources and databases into a cohesive system, possess a basic understanding of front-end technologies like JavaScript, HTML5, and CSS3, and have experience with OAuth2/OIDC for securing the backend using Azure AD B2C. Additionally, expertise in Azure services such as Key Vaults, Cost Management, Budgets, Application Insights, Azure Monitor, VNet, etc., fundamental design principles for scalable applications, database schema creation, unit testing, debugging, Git, Postman, Swagger/OpenAPI, Gen-AI, Langchain, Vectorization, LLMs, NoSQL databases like MongoDB, REST APIs, Microservices, and Azure DevOps for CI/CD will be beneficial for this role. If you are passionate about backend development, have a knack for problem-solving collaboratively, and are committed to delivering high-quality software, we invite you to apply for this exciting opportunity to contribute to our team. (Note: This job description is sourced from hirist.tech),

As a Gen AI Engineer, you will be responsible for developing and implementing AI models using cutting-edge technologies such as GPT-4, ChatGPT, and Hugging Face Transformers. Your primary duties will involve designing and refining AI-generated text prompts, utilizing LangChain for various AI applications, and integrating LlamaIndex to enhance AI solutions. Furthermore, you will work with vector databases and cache databases to efficiently manage large-scale AI data, as well as develop and integrate multi-modal foundation models to support diverse AI applications. Your role will also include applying AI-specific utilities and data analysis methods to improve AI models, developing and managing LLM agents, and collaborating with cross-functional teams to integrate AI solutions into broader applications. To excel in this role, you should have proven hands-on experience with LangChain, proficiency in vector databases and cache databases, and familiarity with multi-modal foundation models and relevant frameworks. Additionally, expertise in designing AI-generated text prompts, using AI utilities such as ChatGPT and Hugging Face Transformers, and developing intelligent agents are essential qualifications. Strong problem-solving, analytical, communication, and collaboration skills are also required to succeed in this fast-paced and innovative environment. If you have a passion for AI technologies, a drive for innovation, and a desire to contribute to cutting-edge AI solutions, this role as a Gen AI Engineer in Indore/Pune could be the perfect opportunity for you.,

About us Bain & Company is a global management consulting firm that assists the world's most ambitious change makers in defining the future. With offices in 65 locations across 40 countries, we collaborate with our clients as a unified team, striving to achieve extraordinary results, surpass the competition, and reshape industries. Since our establishment in 1973, we have gauged our prosperity by the achievements of our clients and uphold the highest level of client advocacy in the industry. In 2004, we inaugurated our presence in the Indian market by launching the Bain Capability Center (BCC) in New Delhi, which is now recognized as BCN (Bain Capability Network) with nodes spread across various geographies. BCN serves as a core and largest unit of Expert Client Delivery (ECD), playing a vital role in enhancing Bain's case teams globally by providing analytics and research solutions in all industries, specific domains for corporate cases, client development, private equity diligence, or Bain intellectual property. The BCN encompasses Consulting Services, Knowledge Services, and Shared Services. Who you will work with Bain & Company stands as the foremost consulting partner to the private equity industry and its stakeholders. The Private Equity Group (PEG) at Bain offers comprehensive advisory services to investors throughout the entire investment lifecycle, including pre-investment strategy, due diligence, post-acquisition value creation, and portfolio management. The PEG Innovation Team (PIT) is a specialized division devoted to supporting the private equity sector and its stakeholders. An essential focus area involves harnessing Generative AI to develop innovative solutions that streamline due diligence, automate processes, and enable data-driven decision-making. By integrating expertise in due diligence, operational enhancement, and cutting-edge technologies like Generative AI, PIT empowers private equity clients to achieve superior returns and maintain a competitive edge in the market. What you'll do This role presents an opportunity to be part of the BCN Data business expanding science capability area within the PIT (PEG Innovation Team). Product Support: The primary responsibility of the team will be to support the Beta production of AI applications for PEG (Private Equity Group) as part of Bain's DD2030 (Due Diligence 2030) initiative. Generative AI Focus: The role involves a significant focus on Generative AI applications, aiming to push the boundaries of innovation in the private equity domain. Broader Automation: Additionally, the role may entail contributing to broader PIT automation initiatives aimed at streamlining processes and enhancing efficiency across various stages of the investment lifecycle. The person in this role will need to: - Translate business objectives into data and analytics solutions, and translate results into business insights using appropriate data engineering, analytics, visualization & Gen AI applications. - Utilize Gen AI skills to design and create repeatable analytical solutions to enhance data quality. - Build and deploy machine learning models using Scikit-Learn for various predictive analytics tasks. - Implement and fine-tune NLP models with Hugging Face to tackle complex language processing challenges. - Collaborate with engineering team members on design requirements to transform PoC methods into repeatable data pipelines; collaborate with the Practice team to develop scalable products. - Aid in creating and documenting standard operating procedures for recurring data processes, and establish a knowledge base of data methods. - Stay updated on advancements in AI/ML technologies and best practices in data science, particularly in LLMs and generative AI. About you A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Applied Mathematics, Econometrics, Statistics, Physics, Market Research, or related field is preferred. 3-5 years of experience in data science & data engineering with hands-on experience in AI/GenAI tools such as Scikit-Learn, LangChain, and Hugging Face. Experience in designing and developing RESTful and GraphQL APIs to facilitate data access and integration. Proficiency in data wrangling in either R or Python is mandatory. Proficiency in SQL is essential, and familiarity with NoSQL data stores is a plus. Familiarity with MLOps practices for model lifecycle management. Experience with Git and modern software development workflow is advantageous. Experience with containerization such as Docker/Kubernetes is beneficial. Proficiency with Agile way of working and tools (Jira, Confluence, Miro). Strong interpersonal and communication skills are imperative. Experience with Microsoft Office suite (Word, Excel, PowerPoint, Teams) is preferred. Ability to explain and discuss Gen AI and Data Engineering technicalities to a business audience. What makes us a great place to work We take pride in consistently being acknowledged as one of the world's best places to work, a proponent of diversity, and a model of social responsibility. Currently ranked as the #1 consulting firm on Glassdoor's Best Places to Work list, we have maintained a position in the top four for the past 12 years. We believe that diversity, inclusion, and collaboration are pivotal in constructing exceptional teams. We recruit individuals with exceptional talents, abilities, and potential, fostering an environment where you can realize your full potential and thrive both professionally and personally. Our commitment to diversity and inclusion has been externally recognized by Fortune, Vault, Mogul, Working Mother, Glassdoor, and the Human Rights Campaign.,

Key Skills : Large Language Models (LLM) : Experience with LangChain, LangGraph Proficiency in building agentic patterns like ReAct, ReWoo, LLMCompiler Multi-modal Retrieval-Augmented Generation (RAG) : Expertise in multi-modal AI systems (text, images, audio, video) Designing and optimizing chunking strategies and clustering for large data processing. Streaming & Real-time Processing : Experience in audio/video streaming and real-time data pipelines Low-latency inference and deployment architectures NL2SQL: Natural language-driven SQL generation for databases Experience with natural language interfaces to databases and query optimization. API Development: Building scalable APIs with FastAPI for AI model serving Containerization & Orchestration: Proficient with Docker for containerized AI services Experience with orchestration tools for deploying and managing services AI Frameworks & Tools: Experience with AI/ML frameworks like TensorFlow, PyTorch Proficiency in LangChain, LangGraph, and other LLM-related technologies Prompt Engineering: Expertise in advanced prompting techniques like Chain of Thought (CoT) prompting, LLM Judge, and self-reflection prompting Experience with prompt compression and optimization using tools like LLMLingua, AdaFlow, TextGrad, and DSPy Strong understanding of context window management and optimizing prompts for performance and efficienc

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 6 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 Note: We are seeking for experience in Agentic AI.