27 Langgraph Jobs

Key Responsibilities: Design and development of AI-driven applications using frameworks such as LangChain, LangGraph, CrewAI, AutoGPT, and Autogen. Build and maintain RESTful APIs, GraphQL endpoints, and gRPC services to support scalable AI features. Support the development of intelligent agents and multi-agent collaboration mechanisms. Implement reasoning techniques including ReAct, Chain-of-Thought (CoT), and Tree-of-Thought (ToT) as part of AI workflows. Contribute to retrieval-augmented generation (RAG) pipelines using vector stores like Weaviate, Pinecone, FAISS, or ChromaDB. Integrate tool-use APIs, function calling, MCP, and external workflows via tools like Zapier or N8N. Work with orchestration tools such as Airflow, Ray, or Temporal to manage agent workflows and data pipelines. Collaborate with AI/ML engineers, product managers, and other developers in building intelligent, production-grade applications. Required Qualifications: 3-5 years of backend or full-stack development experience, with working on Generative or Agentic AI solutions. Proficiency in Python (preferred), with working knowledge of TypeScript/Node.js, Go, or Java. Hands-on experience developing REST APIs, GraphQL endpoints, and/or gRPC-based services. Familiarity with integrating LLMs like GPT-4, Claude, Gemini, Mistral, or LLaMA. Exposure to frameworks such as LangChain, LlamaIndex, or CrewAI. Basic understanding of vector databases and semantic search tools (e.g., FAISS, Pinecone). Experience working in cloud environments (AWS, GCP, Azure) and with containerization tools (Docker, Kubernetes).

Primary Responsibilities: Design and develop AI-driven web applications using Streamlit and LangChain. Implement multi-agent workflows with LangGraph. Integrate Claude 3 (via AWS Bedrock) into intelligent systems for document and image processing. Work with FAISS for vector search and similarity matching. Develop document integration solutions for PDF, DOCX, XLSX, PPTX, and image-based formats. Implement OCR and summarization features using EasyOCR, PyMuPDF, and AI models. Create features such as spell-check, chatbot accuracy tracking, and automatic re-training pipelines. Build secure apps with SSO authentication, transcript downloads, and reference link generation. Integrate external platforms like Confluence, SharePoint, ServiceNow, Veeva Vault, Outlook, G.Net/G.Share, and JIRA. Collaborate on architecture, performance optimization, and deployment. Required Skills: Strong expertise in Streamlit, LangChain, LangGraph, and Claude 3 (AWS Bedrock). Hands-on experience with boto3, FAISS, EasyOCR, and PyMuPDF. Advanced skills in document parsing and image/video-to-text summarization. Proficient in modular architecture design and real-time AI response systems. Experience in enterprise integration with tools like ServiceNow, Confluence, Outlook, and JIRA. Familiar with chatbot monitoring and retraining strategies. Secondary Skills: Working knowledge of PostgreSQL, JSON, and file I/O with Python libraries like os, io, time, datetime, and typing. Experience with dataclasses and numpy for efficient data handling and numerical process

Role & responsibilities Minimum Qualifications: • 23 years of hands-on experience developing production-grade LLM applications. • 3 to 5 years of overall software development experience. • Minimum 1 year of experience in autonomous agent development using the LangGraph framework or similar. Must-Have Skills: 1. Production-Grade LLM Development: Proven experience in developing and deploying large language model applications. 2. Autonomous Agent Development: Hands-on experience with frameworks like LangGraph for building autonomous agents. 3. Advanced RAG Architectures: Expertise in hybrid search, multi-vector retrieval, and contextual compression. 4. Prompt Engineering and Vector Search Optimization: Proficiency in crafting effective prompts and optimizing vector searches. 5. Performance Tuning and Token Optimization: Strong understanding of response caching and techniques to optimize token usage. Nice-to-Have Skills: 1. Scalable Architectures: Experience with Kubernetes, Docker, and cloud platforms, preferably Azure. 2. NoSQL Databases: Familiarity with MongoDB and ElasticSearch. 3. API-Driven Development: Knowledge of building and maintaining APIs. 4. CI/CD Pipelines and Agile Methodologies: Experience with continuous integration/continuous deployment pipelines and Agile practices. 5. Analytical and Problem-Solving Skills: Strong analytical abilities

Responsibilities Job Responsibilities: Architect and Design scalable and efficient AI solutions, leveraging technologies such as LangChain, Agentic AI, RAG, Event driven architecture using Kafka etc. Collaborate with cross-functional teams to identify business needs and develop tailored solutions Provide technical leadership and guidance to junior team members Stay up-to-date with the latest advancements in AI, machine learning, and data science, and apply this knowledge to improve our solutions Communicate complex technical concepts to non-technical stakeholders and team members Troubleshoot and resolve technical issues, and provide support to ensure high system uptime and performance Develop and maintain technical documentation, and ensure that all solutions are well-documented and easily maintainable Technical and Professional Requirements: Preferred Qualifications: Experience with Agentic Frameworks such LangGraph, AutoGen, CrewAI Experience with cloud-based technologies, such as AWS or Azure Familiarity with containerization using Docker, and orchestration using Kubernetes Familiarity with agile development methodologies, such as Scrum or Kanban Experience with AI-related tools and frameworks, such as TensorFlow or PyTorch Knowledge of data engineering, data warehousing, and data governance Experience with agile development methodologies, such as Scrum or Kanban Certification in data science, machine learning, or a related field Experience with leadership and mentoring, with a proven track record of guiding junior team members and helping them grow in their careers Strong business acumen, with the ability to understand business needs and develop solutions that drive business growth and improvement. Preferred Skills: Technology->Artificial Intelligence->Artificial Intelligence - ALL Technology->Machine Learning->Generative AI Technology->Machine Learning->AI/ML Solution Architecture and Design->generative ai Technology->Machine Learning->Python Additional Responsibilities: Required Qualifications: B.E/B.Tech/M.E/M.Tech/MCA degree in Computer Science, Information Technology, or a related field At least 8 years of experience in software development, with at least 2 years of experience in Generative AI Proficiency in LangChain, Python, Generative AI, Agentic AI, Kafka, and Advanced Prompt Engineering Techniques Strong understanding of software architecture, design patterns, and principles Excellent problem-solving skills, with the ability to analyze complex technical problems and develop creative solutions Strong communication and teamwork skills, with the ability to collaborate with cross-functional teams and communicate technical concepts to non-technical stakeholders Tech Skill: LangChain, Python, Fast/Flask API, Gen AI, Agentic AI, Advanced Prompt Engineering, Machine Learning, SQL, Kafka Soft Skill: Communication, Team Work, Problem Solving Educational Requirements Bachelor of Engineering Service Line Information Systems Location of posting is subject to business requirements

Note: Need candidate only from Startup, Banking, Fintech, Product Based We are not looking for NIT or IIT or VIT Candidates. Please don't apply. Required Qualifications: 1+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

Roles and Responsibilities Design and develop data science solutions using Python. Experience in machine learning and deep learning frameworks (PyTorch, TensorFlow) Develop machine learning models using TensorFlow or PyTorch and deploy them on Kubernetes, MLflow, and KServe clusters. Familiarity with machine learning deployment and MLOps tools Experience working with model repositories and fine-tuning frameworks like Hugging Face. Experience with frameworks like LangGraph/LangChain. 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.

We are seeking a highly skilled Generative AI Consulting Director to join our dynamic team, where they will lead our consulting team, manage the delivery of consulting services, guide clients through the implementation of our Gen AI platform, and ensure the successful adoption of the platform across industries. Key Responsibilities: Lead or mentor a global team of AI consultants, solution architects, and professional services teams. Develop and execute the strategy for consulting and professional services for the Gen AI platform. Manage the end-to-end Implementation our platform in client environments, ensuring high quality implementations, on time delivery, and alignment with customer expectations. Work closely with clients to understand their business challenges and design tailored solutions using the Gen AI platform. Lead the development of solution architectures, ensuring that proposed solutions are scalable, innovative, and aligned with the client's objectives. Collaborate with product development, GTM, and engineering teams to ensure successful implementation and integrations. Provide feedback to product teams based on client needs and market trends to continuously improve the platforms offerings. Drive client success by ensuring that Gen AI platform implementation deliver measurable value and return on investment (ROI). Work closely with clients to define successful metrics, track project outcomes, and guide the optimization of AI models and systems post-implementation. Manage P&L for the Consulting and Professional Services division, ensuring profitability through effective project management, cost control, and client retention. Develop and implement strategies to drive revenue growth within the professional services arm. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Mandatory Qualifications/Skills: A bachelors or masters degree, or equivalent, in computer science, Artificial Intelligence, or a related field. 15+ years of experience in consulting or professional services, with at least 5 years in a leadership role overseeing a team of AI consultants or solution architects Extensive experience in delivering Generative AI solutions and familiarity with AI platforms, including knowledge of NLP, deep learning, and reinforcement learning. Experience with large language models (LLMs) and prompt engineering. Solid understanding of various fine-tuning techniques like full fine tuning, PEFT techniques like LoRA, QLoRA and the strategy to adopt for various use cases Proficiency in languages such as Python, Scala, or Java In depth knowledge of both relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., Vector databases, MongoDB, Cassandra etc). Expertise in Gen AI/AI libraries / frameworks, including but not limited to LangChain, LangGraph, LangSmith, TensorFlow, PyTorch, scikit and Keras Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Proven experience in managing client relationships and understanding their business needs to deliver successful AI solutions. Strong understanding of AI systems architecture and the ability to design and implement complex AI solutions for clients across various industries. Experience with project management methodologies, and a proven ability to manage large, complex projects to successful completion. Excellent leadership, mentoring, and team building skills, with a track record of developing high performing teams. Strong business acumen, with the ability to balance technical expertise with client centric decision making. Outstanding communication and presentation skills, capable of engaging with senior executives and non-technical stakeholders. Strong problem solving and analytical skills, with the ability to think creatively and provide innovative solutions Preferred Skills: Knowledge of NVIDIA CUDA, cuDNN, TensorRT, and experience with NVIDIA GPU hardware and the software stack. Familiarity with High Performance Computing (HPC) and their integration of AI workloads. Familiarity with Big Data platforms and technologies, such as Hadoop or Apache Spark and their integration with AI solutions.

About the Job : The Digital workforce team is part of Red Hats Data and AI organization. The team is focused on building and delivering strategic AI agents designed to augment human capabilities, accelerate workflows, and scale operations across the enterprise. In this role, you will work as a member of a highly dynamic, and fast-paced team. As part of the development team, youll need to be creative, motivated, and proficient in architecting and designing cutting-edge applications that leverage Generative AI. You will work closely with different teams, stakeholders, product owners, and program managers to design, document, and develop solutions. We are seeking talented engineers to spearhead the technology and design of key components within Red Hat's Digital Workforce, shaping the future of digital agents. The ideal candidate will possess strong technical abilities, a commitment to quality and open source, a drive for innovation, excellent communication and teamwork skills, and will excel in a dynamic, startup-like setting. What will you do? Architect, design, document, and develop applications in Python and frameworks like LangChain, LangGraph, LLamaStack. Architect and lead the implementation of Agentic AI applications. Architect and lead the implementation of scalable open-source solutions with distributed computing capabilities using Machine Learning models, running on OpenShift AI Architect and design new features with RAG, RAFT, GraphRAG, InstructLab, and their pipelines Develop and optimize retrieval-augmented generation (RAG) pipelines Collaborate with product owners, program managers, different teams, and engineering managers to analyze and clarify business requirements to implement data models and business logic Mentor, influence, and coach a distributed team of engineers Effectively communicate to stakeholders and project team members to ensure proper visibility of development efforts Review code merge requests from other team members for new features Build and deploy applications to Red Hat OpenShift Platform-as-a-Service (PaaS), public clouds, i.e., Google Cloud Platform, AWS, etc. Ensure non-functional requirements, including performance, scalability, resiliency, maintainability, security, etc., are met according to defined standards Resolve bugs, performance problems, and other issues with production applications What will you bring? Strong experience in a software engineering role Bachelor's degree in Computer Science, Computer Engineering or related field 10+ years of professional coding, at least a year using Python Excellent communication skills, solid written and verbal communication skills in English; ability to communicate effectively in a global team Problem-solving and troubleshooting skills including performing root cause analysis Understanding of web application infrastructure and fundamentals like REST and HTTP Understanding of public cloud concepts and development practices Knowledge of Distributed Systems Experience with LangGraph, LangChain, Autogen and/or Python/ Java-based AI libraries for GenAI applications Experience with continuous delivery (CD) like to build and deploy pipelines like Jenkins, Platform-as-a-Service (PaaS) like OpenShift/Kubernetes Presentations skills and public speaking skills for conferences and demos Enjoys solving challenging problems and working with emerging technologies The following are considered a plus: Experience with AI Agentic frameworks Experience with MCP servers Experience working with LLMs Experience in building Chatbots with Slack Personal qualities and communication: Communicate and influence for impact by bringing data to life via clear narratives and/or storytelling Communication skills and experience in interacting with cross functional business and engineering teams Capability in undertaking business needs analysis in direct consultation. Be a self-starter, displaying initiative in seeing needs, building functionality and leading insights for organizational change. Capability to develop a detailed understanding of our business requirements. Excellent communication, presentation, and writing skills.

3+ years of professional frontend development experience Strong skills in React, React Native, TypeScript, HTML, and CSS Experience building mobile and web apps with shared component libraries Required Candidate profile Develop frontend features in React (web) and React Native (mobile) • Build responsive dashboards, mobile tools, and planning interfaces for AI agents • Integrate geospatial visualizations

5+ years of professional experience in software engineering, preferably in ML/AI environments Strong command of Python 3, including data science/ML libraries (Pandas, NumPy, Scikit-learn, proficient in React and OO languages like Java or C# Required Candidate profile Design and develop AI-powered agents to improve decision-making and automation in real world scenarios Build and implement agent workflows using LLMs and orchestration frameworks like LangGraph

Way of working - Work from office (5 days a week) Job Title: Software Development Engineer III Location: Bangalore Tenure: 5 to 7 years Position Overview: As an SDE III at Swiggy, you will play a pivotal role in designing and architecting intelligent systems with a strong emphasis on Agentic AI and multi-agent frameworks. You will contribute to the development of cutting-edge Conversational AI platforms using technologies like Langchain, Langraph, and LLMs from providers such as OpenAI, Anthropic (Claude), Bedrock, Azure, and others. Your responsibilities include owning end-to-end architecture for your team's systems, co-driving the team's technical vision, and transforming product requirements into scalable, production-grade AI solutions. Collaboration with cross-functional product and business teams will be essential to translate product features into intelligent, agent-driven designs and drive the delivery of high-impact applications. What qualities are we looking for . B Tech/M Tech in Computer Science or equivalent from a reputed college with minimum 5+ years of Experience in Product Development Company . Experience working with AI agents, including multi-agent architectures. . Familiarity with agentic AI systems and conversational AI platforms. . Practical knowledge of LLMs (Large Language Models), including integration with providers like OpenAI, Anthropic (Claude), Bedrock, Falsh, and Azure OpenAI. . Strong design skills involving data modeling and low level class design . Good knowledge of object oriented programming and design pa erns . Proficiency in at least one programming language - Python, Java, Golang . Follow industry coding standards and responsible for writing maintainable/scalable/efficient code to solve business problems . Hands-on experience of working with Databases and Linux/Unix platform . Hands-on experience with Langchain or LangGraph for building AI-driven workflows and orchestration. . Strong technical aptitude and good knowledge of CS fundamentals . What will you get to do here . Coming up with best practices to help the team achieve their technical tasks and continually thrive in improving the technology of the product/team. . Driving the adoption of best practices & regular Participation in code reviews, design reviews, architecture discussions. . Experiment with new & relevant technologies and tools, and drive adoption while measuring yourself on the impact you can create . Implementation of long term technology vision for your team. . Creating architectures & designs for new solutions around existing/new areas . Decide technology & tool choices for your team & be responsible for them. Visit our tech blogs to learn more about some of the challenging Problem Statements the team works at:- . https://bytes.swiggy.com/engineering-challenges-at-swiggy-430dea6c86a3 . https://bytes.swiggy.com/the-swiggy-delivery-challenge-part-one-6a2abb4f82f6 . https://bytes.swiggy.com/what-serviceability-means-at-swiggy-c94c1aad352a . https://bytes.swiggy.com/architecture-and-design-principles-behind-the-swiggys-delivery-partner s-app-4db1d87a048a . https://bytes.swiggy.com/swiggy-distance-service-9868dcf613f4 . https://bytes.swiggy.com/the-tech-that-brings-you-your-food-1a7926229886 We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.

Responsibilities: * Develop cutting-edge Agentic AI solutions using Langchain, Langgraph & OpenAI technologies. * Collaborate with cross-functional teams on project delivery and knowledge sharing. Health insurance Work from home

Required Skills 7+ years of professional Python development experience Hands-on experience with at least one agent framework (CrewAI, LangChain, LangGraph, or equivalent) Strong understanding of LLM capabilities, limitations, and prompt engineering Experience with RESTful API design and async Python (FastAPI preferred) Knowledge of vector databases and RAG (Retrieval Augmented Generation) systems Familiarity with financial or tax domains Demonstrated leadership in technical decision-making Excellent written and verbal communication skills Nice to Have Experience with AWS services, particularly Lambda and EKS Background in financial services or tax preparation software Knowledge of security and compliance requirements for financial data Previous startup experience, particularly in MVP development

We are seeking a skilled, motivated, and quick-learner Full Stack Developer to join our team working on cutting-edge Gen AI development work. The successful candidate will be responsible for developing innovative applications and solutions using including frontend and backend. While the solutions will often utilize Retrieval Augmented Generation (RAG), Agentic frameworks the role will not be limited to this, and will involve various AI technologies. Develop and maintain web applications using Angular, NDBX frameworks, and other modern technologies. Design and implement databases in Postgres DB, apply & implement ingestion and retrieval pipelines using pgvector, neo4j, ensuring efficient and secure data practices. Use different generative AI models & frameworks such as LangChain, Haystack, LlamIndex etc for chucking, embeddings, chat completions, integration with different data sources etc. Familiarity and experience with different agentic frameworks and technique like Langgraph, AutoGen, CrewAI, tool using techniques like MCP (Model Context Protocol). Use Azure & AWS cloud platforms in implementation to stay relevant to company AI guidelines requirements. Usage of OpenAPI standards, API first approach to develop APIs for communication between different software components. Collaborate with the team members to integrate various GenAI capabilities into the applications, including but not limited to RAG. Write clean, maintainable, and efficient code that adheres to company standards. Conduct testing to identify and fix bugs or vulnerabilities. Use collaboration and versioning tools such as GitHub for effective team working and code management. Stay updated with emerging technologies and apply them into operations and activities. Show a strong desire for continuous learning and the ability to quickly adapt and implement new technologies. Bachelor's degree in Computer Science, Information Technology, or a related field with 6+ years of working experience. Proven experience as a Full Stack Developer or similar role in designing, developing and deploying end to end applications. Knowledge of multiple front-end languages and libraries (e.g. HTML/ CSS, JavaScript, XML, jQuery). Experience with Angular and NDBX frameworks. Good experience with database technology such as Postgres DB, vector databases. Experience developing APIs following the OpenAPI standards. Understanding & experience in various generative AI models on cloud platforms such as Azure/ AWS, including Retrieval Augmented Generation, Prompt engineering, Agentic RAG, Agentic frameworks, Model context protocols etc. Experience with collaboration and versioning tools such as GitHub Experience with docker images, containers to package up an application with all the parts it needs, such as libraries and other dependencies, and ship it all out as one package. Functional Demonstrated responsiveness and accuracy Strong collaboration and teamwork skills Behaviours Take Ownership & Accountability Assertiveness & Persuasiveness Great attention to detail and problem-solving skills. Self-motivated with a keen interest in learning and implementing new technologies.

Job Type: Full Time Job Description: We are seeking an experienced AI Engineer with 4-5 years of hands-on experience in designing and implementing AI solutions. The ideal candidate should have a strong foundation in developing AI/ML-based solutions, including expertise in Computer Vision (OpenCV). Additionally, proficiency in developing, fine-tuning, and deploying Large Language Models (LLMs) is essential. As an AI Engineer, candidate will work on cutting-edge AI applications, using LLMs like GPT, LLaMA, or custom fine-tuned models to build intelligent, scalable, and impactful solutions. candidate will collaborate closely with Product, Data Science, and Engineering teams to define, develop, and optimize AI/ML models for real-world business applications. Key Responsibilities: Research, design, and develop AI/ML solutions for real-world business applications, RAG is must. Collaborate with Product & Data Science teams to define core AI/ML platform features. Analyze business requirements and identify pre-trained models that align with use cases. Work with multi-agent AI frameworks like LangChain, LangGraph, and LlamaIndex. Train and fine-tune LLMs (GPT, LLaMA, Gemini, etc.) for domain-specific tasks. Implement Retrieval-Augmented Generation (RAG) workflows and optimize LLM inference. Develop NLP-based GenAI applications, including chatbots, document automation, and AI agents. Preprocess, clean, and analyze large datasets to train and improve AI models. Optimize LLM inference speed, memory efficiency, and resource utilization. Deploy AI models in cloud environments (AWS, Azure, GCP) or on-premises infrastructure. Develop APIs, pipelines, and frameworks for integrating AI solutions into products. Conduct performance evaluations and fine-tune models for accuracy, latency, and scalability. Stay updated with advancements in AI, ML, and GenAI technologies. Required Skills & Experience: AI & Machine Learning: Strong experience in developing & deploying AI/ML models. Generative AI & LLMs: Expertise in LLM pretraining, fine-tuning, and optimization. NLP & Computer Vision: Hands-on experience in NLP, Transformers, OpenCV, YOLO, R-CNN. AI Agents & Multi-Agent Frameworks: Experience with LangChain, LangGraph, LlamaIndex. Deep Learning & Frameworks: Proficiency in TensorFlow, PyTorch, Keras. Cloud & Infrastructure: Strong knowledge of AWS, Azure, or GCP for AI deployment. Model Optimization: Experience in LLM inference optimization for speed & memory efficiency. Programming & Development: Proficiency in Python and experience in API development. Statistical & ML Techniques: Knowledge of Regression, Classification, Clustering, SVMs, Decision Trees, Neural Networks. Debugging & Performance Tuning: Strong skills in unit testing, debugging, and model evaluation. Hands-on experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone). Good to Have: Experience with multi-modal AI (text, image, video, speech processing). Familiarity with containerization (Docker, Kubernetes) and model serving (FastAPI, Flask, Triton).

Role & responsibilities Expertise in Data Analysis, Statistics, Computer Vision, AI & Machine Learning Concepts Unflinching zeal to learn, to try out Proof of Technology for new and emerging AI/ML Design and develop applications powered by Large Language Models (LLMs) like GPT-4, Claude, Gemini, and open-source models (LLaMA, Mistral, etc.) Implement RAG pipelines using LangChain and LangGraph for production-ready applications. Build and orchestrate autonomous and tool-using LLM agents. Integrate with vector databases (e.g., Pinecone, Chroma, Weaviate, FAISS) for semantic search and memory storage. Use tools like OpenAI Function Calling, React, or LangGraph Agents for decision-based workflows. Deploy applications using cloud platforms (Azure, AWS, GCP) with APIs, microservices, or serverless functions. Collaborate with product and design teams to develop chatbots, copilots, and multimodal interfaces. Monitor performance, cost, latency, and evaluate prompt effectiveness through prompt engineering best practices. Fine-tune, quantize, or use adapters (LoRA, PEFT) for open-source models where applicable. Stay up-to-date with the latest advancements in Gen AI, MLOps, and AI safety principles. Preferred candidate profile Bachelor's/Master's degree in Computer Science, Mathematics, Statistics, or a related field. 4-9 years of experience as a Data Scientist with strong skills in Python, NLP, Deep Learning, and Statistics. Hands-on experience with Generative AI, LangChain, LangGraph, and building LLM Agents for real-world AI applications. Strong Python skills with experience in deploying Gen AI apps using frameworks like FastAPI or Streamlit. Expertise in Retrieval-Augmented Generation (RAG) and working with vector databases like Pinecone, FAISS, or Chroma. Deep understanding of prompt engineering, OpenAI function calling, and chaining logic for dynamic interactions. Familiarity with cloud platforms such as Azure and AWS and deploying models to these platforms. Strong problem-solving and analytical skills with excellent communication and presentation skills. Disclaimer: The following job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances

Hexaware is conducting Walkin Interview for Data Scientist (GENAI)/ Lead Data Scientist (GENAI)/ Data Scientist Architect (GENAI) _Noida Location_12th April 2025 (Saturday) We urgently looking for Immediate joiners/Early joiners. Interested Candidates can share CV at umaparvathyc@hexaware.com MUST HAVE 1. Strong experience in Data Scientist (GENAI) 2. Strong hands-on experience in GenAI LLM models (ChatGPT, LLAMA 2, etc.), Vector databases, LangChain, LangGraph, and LlamaIndex, Azure/AWS, Bedrock, GPT-4. 3. Strong in python, Machine learning, deep Learning architecture, NLP, and OCR. Primary Skills 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. Python Fast API experience, SDA based implementations for all the APIs Architect should be hand-on to review the code developed by the developers Should be able to take and work on spike stories assigned to him/her.

Very Urgent: Python-trained Freshers / Jr.Python Developers Company: AurumData Solutions Location: Hyderabad Experience: 1-5 Years Work type: Work From Office Key skills: Python, AI, API/FastAPI, SQL/PostgreSQL, Javascript, HTML, CSS, BCrypt, numpy, matplotlib, PyTorch and Tensorflow, Integration, etc.. . Description: We are looking for (1-5 years or 0 years but strong Python/Full Stack developer background) to join our engineering team and help us create AI driven Web applications. Following are the criteria we are looking for: 1. Strong base in engineering and test-driven development of python applications. 2. Working knowledge of integrating AI models into full stack applications. 3. Experience in developing React Web applications and optimization of UI. 4. Good understanding of networking and debugging of full stack application. 5. Ability to virtualize and create application and service images. 6. Experience working in agile engineering workflows and dealing with dynamic requirements. 7. Good communication and team interaction Tool knowledge: 1. Python JUnit or similar unit test case framework, FastAPI, BCrypt, numpy, matplotlib, transformer model integration, PyTorch and Tensorflow, Triton server deployment and integration, CUDA integrations. 2. React Web application development, component driven development, State management with libraries like Redux 3. PostgreSQL, schema optimization 4. Docker, Git, VS Code Thanks & Regards, Madhavi Cheruku Talent Acquisition Lead Mobile No: +91- 6281840572 Email: madhavi@aurumdatasolutions.com Aurum Data Solutions (I) Pvt Ltd., (a subsidiary of Aurum Data Solutions Inc, USA) Unit #06B, The Headquarters, 10th floor, Wing-B, Orbit by Auro, Knowledge City, Raidurga, Hyderabad 500 019.

Very Urgent: AI Tech Specialist Company: AurumData Solutions Location: Hyderabad Experience: 10-15 Years (5+years in AI) Work type: Work From Office Key skills: AI, Python, Data analysis, LLM, TensorFlow, PyTorch, SQL, RAG, NLP, LangChain, LangGraph, SQL etc.. # AI Specialist Position Analysis This job description outlines a role for an AI Specialist who will be responsible for developing and implementing AI solutions across various domains. Here's a breakdown of the key aspects: ## Core Responsibilities - Developing AI models and algorithms - Implementing machine learning techniques for data analysis - Creating NLP applications (chatbots, virtual assistants) - Data preprocessing and feature engineering - Model evaluation and optimization - Research and innovation in AI - Cross-functional collaboration - Technical documentation ## Required Skills - Strong background in machine learning and deep learning - Python programming with frameworks like TensorFlow and PyTorch - Independent project management capabilities - Data science workflow experience - Cloud platform knowledge (AWS, Google Cloud, Azure) - Problem-solving with practical solutions - **Experience with vector databases** - **Knowledge of Large Language Models (LLMs)** - **Implementation of Retrieval-Augmented Generation (RAG) systems** - **Experience with LLM fine-tuning techniques** - **Expertise in fine-tuning LLMs for specific domains/tasks** - **Front-end development skills** for AI application interfaces - **Proficiency with Pydantic** for data validation and settings management - **Experience developing agentic frameworks** for autonomous AI systems - **Familiarity with LangChain** for building LLM applications - **Knowledge of Hugging Face** ecosystem and model hub - **Experience with LangGraph** for building complex, multi-agent systems ## Qualifications - Bachelor's or Master's in Computer Science, AI, or related fields - Experience in startup environments - Passion for AI applications This position combines traditional machine learning expertise with cutting-edge LLM technologies and practical application development skills. The role requires experience across the full AI development stack, from data management and model fine-tuning to building sophisticated agent-based systems and user-facing applications. If you are interested, kindly send your CVs to Balaram@aurumdatasolutions.com Regards, Balaram K Mobile No: +91- 9000749410 / 9848771366 USA: +1 (346) 999 0801 Email: Balaram@aurumdatasolutions.com

Job Description: GenAI Developer (LangChain, LangGraph, VectorDB, LLMs, MCP, Embedding, RAG) Position Overview: We are looking for an experienced and motivated GenAI Developer to join our team in building cutting-edge applications powered by GenAI technologies. As a GenAI Developer, you will work with LangChain, LangGraph, Vector Databases, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to create intelligent, scalable, and efficient AI-driven applications. You will play a key role in integrating these advanced technologies into real-world use cases, including text generation, knowledge retrieval, and recommendation systems. Key Responsibilities: LangChain Development: Develop GenAI applications using LangChain, including building chains, agents, and integrations for a variety of use cases. LangGraph Development: Utilize LangGraph for building workflow agents, controlling states, and developing intelligent decision-making systems. Vector Database Integration: Design, implement, and maintain vector database solutions (e.g., Qdrant, Pinecone, FAISS) for efficient storage and retrieval of embeddings. LLM Integration: Leverage LLMs to generate high-quality outputs for various use cases, such as conversational agents, document summarization, or content generation. Embedding Building: Develop embeddings for text, images, and other media to integrate into retrieval systems and enhance search relevance and accuracy. RAG Implementation: Design and implement RAG workflows to improve accuracy and context in AI applications by combining real-time retrieval with language model generation. MCP Integration: Work with the Microsoft Cognitive Platform (MCP) for AI and cognitive services, integrating them with LangChain and LangGraph for enhanced capabilities. Optimization & Fine-Tuning: Continuously optimize AI models, embeddings, and retrievers for performance and efficiency. Collaboration & Problem-Solving: Work closely with product managers, data scientists, and other engineers to understand business needs and deliver AI-driven solutions. Required Skills & Qualifications: Technical Skills: LangChain : Hands-on experience with LangChain for developing intelligent workflows, managing chains, and leveraging its powerful capabilities for building GenAI applications. LangGraph : Proficiency in LangGraph for designing advanced workflows and agents with state management, decision-making, and loops. Vector Databases (e.g., Qdrant, Pinecone, FAISS) : Experience working with vector databases to manage and search embeddings, and optimize large-scale retrieval tasks. Large Language Models (LLMs) : In-depth understanding of LLMs, such as GPT, BERT, and other transformer-based architectures, and how to integrate them into GenAI applications. Embedding Creation and Integration : Expertise in building embeddings using models like sentence-BERT, OpenAI embeddings, or custom models for a variety of data types (text, images, etc.). Retrieval-Augmented Generation (RAG) : Proven experience in designing and implementing RAG systems that combine real-time retrieval with language model generation. Microsoft Cognitive Platform (MCP) : Familiarity with integrating Microsoft Cognitive Services, such as Azure Cognitive Search, Azure OpenAI, or other Microsoft AI tools, into GenAI applications. Model Context Protocol (MCP) - Building or exposing Resources , Prompts , tools to LLM based AI Agents . Natural Language Processing (NLP) : Strong understanding of NLP techniques, including text classification, entity recognition, sentiment analysis, and text summarization. AI Model Optimization : Experience in model fine-tuning, prompt engineering, and optimizing LLMs for specific tasks. APIs & Microservices : Familiarity with designing and consuming RESTful APIs, and microservice architecture for scalable AI solutions. Additional Skills: Cloud Platforms (Azure, AWS, GCP) : Experience deploying GenAI applications on cloud platforms such as Azure, AWS, or Google Cloud, with an emphasis on cloud-based AI solutions. Machine Learning Frameworks : Knowledge of popular ML frameworks, such as TensorFlow, PyTorch, or Hugging Face, and how to use them for model training and inference. Data Engineering : Strong skills in handling large datasets, including data preprocessing, data cleaning, and data augmentation, to support AI model training. Version Control : Proficiency with Git and GitHub for version control, collaborative development, and code review processes. Problem-Solving & Analytical Thinking : Excellent problem-solving skills with a strong analytical mindset to break down complex AI challenges into manageable components. Collaboration & Communication : Strong teamwork and communication skills to effectively collaborate with cross-functional teams and deliver high-impact solutions. Preferred Qualifications: Advanced Degree : A degree in Computer Science, Data Science, AI, or a related field. GenAI Application Development : Experience in building AI-driven applications or platforms with a focus on generative models, search systems, and conversational AI. Familiarity with LlamaIndex, FAISS, or Similar Tools : Knowledge of popular vector search tools and libraries beyond LangChain and LangGraph is a plus.

Roles and Responsibilities : Design, develop, test, and deploy AIML (Artificial Intelligence Markup Language) solutions using Python programming language. Collaborate with cross-functional teams to integrate AIML models into existing systems and applications. Develop predictive models using regression techniques to solve complex business problems. Troubleshoot issues related to AIML model performance, data quality, and system integration. Job Requirements : 5-7 years of experience in developing AIML-based applications or similar technologies. Strong proficiency in Python programming language with expertise in ML libraries such as scikit-learn or TensorFlow. Experience with building predictive models using regression techniques for solving real-world problems.

Role: Agentic AI Engineer-Healthcare Exp: 4-10 years Location: Hyderabad, India (Onsite) Job Description: Role and Responsibilities: Design Agentic AI Systems for Healthcare Develop frameworks for efficient agent-to-agent communication, dynamic task assignment, and context-aware decision-making, with a focus on improving healthcare operations and patient outcomes. Leverage tools such as LangGraph, AutoGen, and OpenAI Swarm to enhance decision support systems in clinical environments. Implement Retrieval-Augmented Generation (RAG) pipelines and memory management techniques to ground agents in healthcare-specific knowledge (e.g., medical literature, patient records, treatment protocols). Build Versatile AI Capabilities for Healthcare Work with Vision-Language Models (VLMs) to analyze medical imaging (e.g., X-rays, MRIs) alongside text-based reasoning to assist in tasks such as anomaly detection, diagnosis support, and treatment planning. Create autonomous agents capable of executing complex healthcare tasks, such as data analysis, patient record management, or clinical decision support, triggered by real-time health data or environmental factors. Optimize AI for Real-World Healthcare Impact Deploy scalable AI workflows in cloud environments (AWS/GCP), ensuring robust performance for time-sensitive healthcare applications, such as real-time patient monitoring or critical care support. Implement observability tools like LangSmith to track agent behavior, identify anomalies, debug failures, and enhance the reliability and safety of AI systems in healthcare settings. Human-in-the-Loop Intelligence in Healthcare Design mechanisms to integrate human oversight into AI systems, ensuring that healthcare professionals can intervene when necessary. Implement features like bias testing, fallback protocols, and explainability to balance autonomy with safety and ethical considerations. Leverage tools like LangSmith for real-time monitoring and debugging of AI agents to optimize performance and reduce risk in clinical and healthcare-related environments. Proven AI Development Experience: Demonstrate a portfolio of projects highlighting expertise in multi-agent systems, RAG implementations, and decision automation, specifically applied to healthcare (GitHub/Kaggle links required). Proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow, Hugging Face) with a focus on healthcare applications. Technology/Skills Required: Experience with cloud platforms (AWS, GCP) and vector databases (Pinecone, Milvus) in healthcare contexts, managing patient data, clinical workflows, and medical knowledge. Familiarity with agentic frameworks (LangChain, CrewAI) and large language model orchestration to enhance clinical decision support systems. Interested candidate can drop the CV at saepoori@theaesgroup.com or notify+JzW2LVeiJVHx@atsapplications.com

AI Engineer, for an early-stage Generative AI startup who can help us translate Product specs into a high-performing and scalable product. Also help in improving functionality of product. End goal is to achieve product-market objectives.

Project Description: Grid Dynamics aims building enterprise generative AI framework to deliver innovative, scalable and efficient AI-driven solutions across business functions.Due to constant scaling of digital capabilities the platform requires enhancements to incorporate cutting-edge generative AI features and meet emerging business demands. Platform should onboard brand new capabilities like Similarity Search (image,video and voice);Ontology and entity managment;voice and file mgmt [text to speech & vice-versa, metadata tagging, multi-media file support];Advanced RAG ; Multi-Modal capabilities Responsibilities: As an LLMOps Engineer, you will be responsible for providing expertise on overseeing the complete lifecycle management of large language models (LLM). This includes the development of strategies for deployment, continuous integration and delivery (CI/CD) processes, performance tuning, and ensuring high availability of our LLM services. You will collaborate closely with data scientists, AI/ML engineers, and IT teams to define and align LLM operations with business goals, ensuring a seamless and efficient operating model. In this role, you will: Define and disseminate LLMOps best practices. Evaluate and compare different LLMOps tools to incorporate the best practices. Stay updated on industry trends and advancements in LLM technologies and operational methodologies. Participate in architecture design/validation sessions for the Generative AI use cases with entities. Contribute to the development and expansion of GenAI use cases, including standard processes, framework, templates, libraries, and best practices around GenAI. Design, implement, and oversee the infrastructure required for the efficient operation of large language models in collaboration with client entities. Provide expertise and guidance to client entities in the development and scaling of GenAI use cases, including standard processes, framework, templates, libraries, and best practices around GenAI Serve as the expert and representative on LLMops Practices, including: (1) Developing and maintaining CI/CD pipelines for LLM deployment and updates. (2) Monitoring LLM performance, identifying and resolving bottlenecks, and implementing optimizations. (3) Ensuring the security of LLM operations through comprehensive risk assessments and the implementation of robust security measures. Collaborate with data and IT teams to facilitate data collection, preparation, and model training processes. Practical experience with training, tuning, utilizing LLMs/SLMs. Strong experience with GenAI/LLM frameworks and techniques, like guardrails, Langchain, etc. Knowledge of LLM security and observability principles. Experience of using Azure cloud services for ML Experience of using Azure cloud services for ML Min requirements: Programming languages: Python Public Cloud: Azure Frameworks: K8s, Terraform, Arize or any other ML/LLM observability tool Experience: Experience with public services like Open AI, Anthropic and similar, experience deploying open source LLMs will be a plus Tools: LangSmith/LangChain,guardrails Would be a plus: Knowledge of LLMOps best practices. Experience with monitoring/logging for production models (e.g. Prometheus, Grafana, ELK stack) We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office

Project Description: Grid Dynamics wants to build a centralized, observable and secure platform for their ML, Computer Vision, LLM and SLM models. Grid Dynamics wants to onboard a vast number of AI agents, able to cover multiple required skills, ensuring a certain level of control and security in regards to their usage and availability. The observable platform must be vendor-agnostic, easy to extend to multiple type of AI applications and flexible in terms of technologies, frameworks and data types. This project is focused on establishing a centralized LLMOps capability where every ML, CV, AI-enabled application is monitored, observed, secured and provides logs of every activity. The solution consists of key building blocks such monitor every step in a RAG, Multimodal RAG or Agentic Platform, track performances and provide curated datasets for potential fine-tuning. Alignment with business scenarios, PepVigil provides also certain guardrails that allow or block interactions user-to-agent, agent-to-agent or agent-to-user. Also, Guardrails will enable predefined workflows, aimed to give more control over the series of LLM chains. Details on Tech Stack Job Qualifications and Skill Sets Advanced degree in Data Science, Computer Science, Statistics, or a related field Setting up Agent Mesh (LangSmith) Setting up Agent communication protocols (JSON/XML etc) Setting up message queues, CI/CD pipelines (Azure Queue Storage, Azure DevOps) Setting up integrations Langgrah, LangFuse Knowledge on Observability tool Arize-Phoenix tools Managing Agent Registry, Integrating with AgentAuth framework like Composio Setting up AgentCompute (Sandpack, E2BDev, Assistant APIs) Integration with IAM (Azure IAM, OKTA) Performing/Configuring Dynamic Orchestration and agent permissions Tech Stack Required: ML MLOPs Agent (Agent / Agent Mesh) LangFuse, LanChain, LangGraph Deployments (Docker, Jenkins, Kubernetes) Cloud Platforms: Azure/AWS/GCP We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office