20 Crewai Jobs

We are seeking a highly skilled and motivated Senior Data Scientist with 56 years of experience to drive the development of intelligent AI systems. This role requires extensive hands-on experience with Large Language Models (LLMs) , strong background in Agentic AI , Machine Learning , and Python programming . You will work on designing autonomous agents, building scalable ML pipelines, and integrating advanced LLM-powered solutions into real-world products. Key Responsibilities: Architect and implement agentic AI systems that use LLMs for autonomous reasoning, planning, and multi-step task execution. Lead the development, fine-tuning, evaluation, and deployment of Large Language Models (LLMs) using frameworks like Hugging Face Transformers, LangChain, LLM orchestration tools, and vector databases. Develop ML models using supervised, unsupervised, and reinforcement learning techniques, and integrate them into production environments. Design and build end-to-end machine learning pipelines, including data ingestion, feature engineering, training, and deployment. Optimize model performance and latency in real-world applications and implement model monitoring and retraining strategies. Collaborate with cross-functional teams including product, engineering, and business to translate AI capabilities into product features. Mentor junior data scientists and contribute to the team's technical excellence and innovation. Required Skills & Experience: 56 years of professional and relevant experience in data science, AI, or machine learning roles. Proven hands-on experience with LLMs, including fine-tuning, prompt engineering, and RAG (Retrieval-Augmented Generation) pipelines. Deep expertise in Python and ML libraries such as scikit-learn, PyTorch, TensorFlow, and transformers. Strong understanding of agentic AI principles, autonomous agents, and task orchestration. Experience with cloud platforms (AWS, GCP, or Azure) and scalable infrastructure for deploying AI models. Exposure to API development, ML model serving, and integration with real-time systems. Excellent communication and collaboration skills in cross-functional environments. Educational Qualification: Bachelor of Technology (B.Tech) in Computer Science, Data Science, Artificial Intelligence, or a related field from a recognized institution. Preferred Qualifications: Contributions to open-source AI/ML projects or research publications related to LLMs or agent-based systems. Familiarity with LangChain, AutoGPT, CrewAI, or other agent orchestration frameworks. Experience with vector databases (e.g., FAISS, Pinecone) and knowledge of semantic search. Understanding of multi-agent collaboration, goal decomposition, and planning architectures.

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).

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

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Job Title : Senior Software Engineer. Exp: 5 Years to 10 Years Location : Remote. About the Company: Galileo is the leading platform for Gen AI evaluation and observability, with a mission to democratize building safe, reliable and robust applications in the new era of AI powered software development. Our foundation is built on pioneering the early technology behind the world's most ubiquitous AI applications including Apple's Siri and Google Speech. We firmly believe that AI developers require meticulously crafted, research-driven tools to create trustworthy and high-quality generative AI applications that will revolutionize our work and lifestyle. Galileo addresses the complexities inherent in implementing, evaluating, and monitoring GenAI applications, optimizing the development process for both individual developers and teams by offering a comprehensive platform that spans the full AI development lifecycle. Galileo bridges critical gaps, significantly enhancing developers' ability to refine and deploy reliable and precise GenAI applications. Since its inception, Galileo has rapidly gained traction, serving Fortune 100 banks, Fortune 50 telecom companies, as well as AI teams at prominent organizations such as Reddit and Headspace Health, among dozens of others. Galileo has AI research at its core, with the founders coming from Google and Uber where they solved challenging AI/ML problems in the Speech, Evaluation and ML Infra domains. It is now a Series B business backed by tier 1 investors including Battery Ventures, Scale Venture Partners, and Databricks Ventures, with $68M in total funding. We are headquartered in San Francisco with locations such as New York and Bangalore, India forming our areas of future growth. Responsibilities Understand GenAI at a sufficient level of curiosity and usage (beyond simple applications such as using ChatGPT such as understanding and usage of Lang Chain, Lang Graph, Crew AI, OpenAI APIs etc. Be able to quickly understand our product hosted at https://app.galileo.ai/ Have 5 years of experience working on Product Engineering teams building service oriented or general micro services-based applications using Python Can work in a fast-paced environment and can get ideas quickly off the ground with minimal support (ideally has experience working in a mix of large enterprises and startup experience). Skill Requirements Programming languages: Python and Typescript Basic understanding of LLM (OpenAI/Gemini/) API and SDK Basic understanding of AI frameworks like Langchain, CrewAI etc. Has some exposure and understanding of Observability and Reliability (such as familiarity with OTEL, understanding of SLOs) Has some degree of familiarity with Cloud environments such as Azure, GCP and AWS If you are passionate about applying your experience in the AI/ML field to an emerging and advancing field of Generative AI, this is a great opportunity for you. You will get to work on a ground breaking product poised to revolutionize the way companies approach LLM Evaluations. Join our team at Galileo and help us build the future of Evaluations in Generative AI.

Job Title: AI Developer Supply Chain Management Location: Permanent Remote Job Type: Full-time Team: Product AI Engineering We are looking for a talented LLM Developer to join our AI Engineering team and contribute to the development of the SCM Expert AI Agent the core brain behind AI capabilities like demand forecasting, anomaly detection, ETA prediction, and route optimization in the FarmToPlate (F2P) platform. In this role, you will focus on integrating and optimizing LLM-based agentic architectures using frameworks like LangChain, CrewAI, and RAG pipelines. Youll work closely with traditional ML developers and backend engineers to deploy intelligent, explainable, and real-time decision agents for supply chain management. Responsibilities: Design, build, and optimize LLM-based agents using LangChain, CrewAI, or custom wrappers. Implement RAG pipelines with vector stores (e.g., FAISS, ChromaDB) and embedding models. Develop LLM-powered tools for demand forecasting, query understanding, anomaly explanations, and summarization. Integrate agents with internal and external data sources using tools like MongoDB, Sklearn datasets, or Browsing Agents. Implement prompt engineering, agent memory, and context-chaining for more dynamic agent behavior. Collaborate with data science and product teams to translate SCM logic into agentic workflows. Expose models and agents through APIs using FastAPI, including role-based access if needed. Optimize runtime performance with quantization, PEFT (parameter-efficient finetuning), and model caching. Track experiments, versions, and deployment artifacts using tools like MLflow, SageMaker, or custom registries. Requirements: 3-5 years of experience working on Python-based AI systems. Strong understanding of LLMs, Transformers, Prompt Engineering, and conversational AI. Hands-on experience with LangChain, CrewAI, OpenAI/GPT APIs, or Hugging Face Transformers. Familiarity with RAG concepts, vector databases (FAISS, Chroma), and embedding techniques. Good knowledge of API frameworks (FastAPI/Flask) and working with JSON schema-driven inputs. Basic understanding of traditional ML models and workflows (e.g., regression, classification, anomaly detection). Comfortable integrating external data tools and APIs into LLM pipelines. Bonus Points For Experience building Agentic RAG systems that combine logic, tools, memory, and models. Knowledge of Open Source LLM tuning using PEFT, LoRA, bitsandbytes, Unsloth, etc. Familiarity with SageMaker, EKS, or deploying custom models to the cloud. Experience in supply chain/logistics, or working with ERP/SCM structured data. Built monitoring dashboards using Evidently.ai or similar model observability tools. Why Join Us Be part of a domain-driven AI platform blending supply chain expertise with modern agentic LLM architectures. Work on real-world use cases that impact farm-to-plate food systems at scale. Collaborate with a fast-moving, cross-functional team that values innovation, ownership, and outcome. Learn and grow in a modular, full-stack AI environment where your ideas become deployed APIs. Enjoy flexibility in remote, experimentation, and continuous learning.

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

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 Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Role & responsibilities : Hiring for GenAI Engineering Lead/ Architect (Must have - Autogen,CrewAI and WrenAI) Experience - 7 to 10 Years. Hybrid mode of work. This role requires hands-on project expertise to implement an enterprise application built on top of SQL and unstructured data (images,videos,logs etc.) using Autogen, CrewAI, Azure OpenAI GPT-4 Turbo and GPT-4V with PTUs. This is a hands-on architect role requiring both deep technical skills and the ability to deliver complex AI applications end-to-end on large operational databases to render charts, tables and other insights as completions from NLP-based prompts. Deep experience of Autogen and Azure AI Search is a MUST. This is not a document retrieval, summarization or semantic search-based role. Please share your CV to ranjitha@promantusinc.com Regards, Ranjitha. 7619598141

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

We are seeking experienced AI Engineer to design, develop & implement intelligent agents to enhance our video intelligence capabilities. Hands-on experience with both closed & open-source LLMs and production-grade agent implementation Required Candidate profile Experience working with LLMs (both closed models like GPT-4, Claude, & open-source models like Llama, Mistral) Production-grade agent implementation using frameworks such as LangChain, CrewAI, n8n

Job Description: We are looking for a talented and motivated Python Developer with a strong background in AI technologies to join our dynamic team. As a Python Developer focusing on AI, you will work on building and improving AI-driven applications, particularly those utilizing agent-based systems, CrewAI, and AutoGen technologies. 'Your primary responsibility will be to design, develop, and implement intelligent solutions that can adapt, automate, and enhance processes within various systems,Design and develop AI applications using Python, leveraging frameworks like CrewAI and AutoGen to create intelligent and autonomous systems. Implement and optimize agent-based systems to simulate complex behavior and interactions in real-world scenarios. Build and integrate AI models into applications, ensuring performance, scalability, and reliability. Develop and maintain APIs for AI and automation services. Collaborate with cross-functional teams, including data scientists and other developers, to deliver cutting-edge AI-powered solutions. Continuously improve system performance through optimizations and the integration of advanced AI techniques. Troubleshoot and debug issues in AI-driven systems and ensure timely resolution. Stay up to date with the latest AI trends and advancements, particularly around agent-based systems, CrewAI, and AutoGen.

ob Description: We are looking for a talented and motivated Python Developer with a strong background in AI technologies to join our dynamic team. As a Python Developer focusing on AI, you will work on building and improving AI-driven applications, particularly those utilizing agent-based systems, CrewAI, and AutoGen technologies. Your primary responsibility will be to design, develop, and implement intelligent solutions that can adapt, automate, and enhance processes within various systems. Key Responsibilities: Design and develop AI applications using Python, leveraging frameworks like CrewAI and AutoGen to create intelligent and autonomous systems. Implement and optimize agent-based systems to simulate complex behavior and interactions in real-world scenarios. Build and integrate AI models into applications, ensuring performance, scalability, and reliability. Develop and maintain APIs for AI and automation services. Collaborate with cross-functional teams, including data scientists and other developers, to deliver cutting-edge AI-powered solutions. Continuously improve system performance through optimizations and the integration of advanced AI techniques. Troubleshoot and debug issues in AI-driven systems and ensure timely resolution. Stay up to date with the latest AI trends and advancements, particularly around agent-based systems, CrewAI, and AutoGen. Key Skills Required: Proficiency in Python, with a strong understanding of Python libraries and frameworks (such as NumPy, Pandas, TensorFlow, Keras, or PyTorch). Solid experience with agent-based systems and related concepts in AI. Familiarity with CrewAI and AutoGen technologies (or similar AI frameworks). Experience with building and deploying AI models, including both supervised and unsupervised learning. Knowledge of machine learning algorithms, deep learning, and neural networks. Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI applications. Familiarity with version control systems like Git. Strong problem-solving skills and ability to work in a fast-paced environment. Good communication skills and the ability to work collaboratively within a team. Qualifications Bachelor's degree in Computer Science, Engineering, or a related field. Experience with machine learning frameworks such as Agent-CrewAi, Autogen,TensorFlow, PyTorch, or Scikit-Learn. Proven experience with Python programming language. Strong understanding of statistical and mathematical principles. Experience with data handling libraries such as Pandas and NumPy. Excellent problem-solving skills. Strong communication and teamwork abilities.

Job Title: AI Developer Supply Chain Management Location: Permanent Remote Job Type: Full-time Team: Product AI Engineering We are looking for a talented LLM Developer to join our AI Engineering team and contribute to the development of the SCM Expert AI Agent the core brain behind AI capabilities like demand forecasting, anomaly detection, ETA prediction, and route optimization in the FarmToPlate (F2P) platform. In this role, you will focus on integrating and optimizing LLM-based agentic architectures using frameworks like LangChain, CrewAI, and RAG pipelines. Youll work closely with traditional ML developers and backend engineers to deploy intelligent, explainable, and real-time decision agents for supply chain management. Responsibilities: Design, build, and optimize LLM-based agents using LangChain, CrewAI, or custom wrappers. Implement RAG pipelines with vector stores (e.g., FAISS, ChromaDB) and embedding models. Develop LLM-powered tools for demand forecasting, query understanding, anomaly explanations, and summarization. Integrate agents with internal and external data sources using tools like MongoDB, Sklearn datasets, or Browsing Agents. Implement prompt engineering, agent memory, and context-chaining for more dynamic agent behavior. Collaborate with data science and product teams to translate SCM logic into agentic workflows. Expose models and agents through APIs using FastAPI, including role-based access if needed. Optimize runtime performance with quantization, PEFT (parameter-efficient finetuning), and model caching. Track experiments, versions, and deployment artifacts using tools like MLflow, SageMaker, or custom registries. Requirements: 3-5 years of experience working on Python-based AI systems. Strong understanding of LLMs, Transformers, Prompt Engineering, and conversational AI. Hands-on experience with LangChain, CrewAI, OpenAI/GPT APIs, or Hugging Face Transformers. Familiarity with RAG concepts, vector databases (FAISS, Chroma), and embedding techniques. Good knowledge of API frameworks (FastAPI/Flask) and working with JSON schema-driven inputs. Basic understanding of traditional ML models and workflows (e.g., regression, classification, anomaly detection). Comfortable integrating external data tools and APIs into LLM pipelines. Bonus Points For Experience building Agentic RAG systems that combine logic, tools, memory, and models. Knowledge of Open Source LLM tuning using PEFT, LoRA, bitsandbytes, Unsloth, etc. Familiarity with SageMaker, EKS, or deploying custom models to the cloud. Experience in supply chain/logistics, or working with ERP/SCM structured data. Built monitoring dashboards using Evidently.ai or similar model observability tools. Why Join Us Be part of a domain-driven AI platform blending supply chain expertise with modern agentic LLM architectures. Work on real-world use cases that impact farm-to-plate food systems at scale. Collaborate with a fast-moving, cross-functional team that values innovation, ownership, and outcome. Learn and grow in a modular, full-stack AI environment where your ideas become deployed APIs. Enjoy flexibility in remote, experimentation, and continuous learning.

Job Description & Responsibilities Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams. Qualification, Skills & Experience Good hands-on experience in Advanced Python Programming Experiences in scalable Microservice Architecture and Development Good understanding of API Development, Messaging Queues and Asynchronous Task Management Basic DevOp skills and working with Docker Experience with LangChain, LangGraph, AutoGen or CrewAI are a big plus Ability to co-work in a small team with different locations Ability to learn and understand a new Python framework

We are seeking a proficient AI/ML Engineer responsible for testing, deploying, and hosting various Large Language Models (LLMs). The role involves monitoring deployed agentic services, ensuring their optimal performance, and staying abreast of the latest advancements in AI technologies. Key Responsibilities: LLM Deployment & Hosting Evaluate, test, and deploy diverse LLMs on cloud-based and on-premise infrastructures. Optimize model performance for scalability and efficiency. Implement secure API endpoints and model-serving pipelines. Strong CI/CD skills and knowledge of CI/CD tools like Jenkins, GitHub Actions, CircleCI etc. Agentic AI Services Deploy and maintain AI agents using frameworks such as CrewAI, Agnos(Phi Data), AutoGen etc. Integrate LLMs into business workflows and automation tools. Design, monitor, and enhance agentic services for real-world applications. Monitoring & Optimization Utilize advanced observability tools to monitor model performance, latency, and cost efficiency. Implement tools like AgentOps, OpenLIT, Langfuse, and Langtrace for comprehensive monitoring and debugging of LLM applications. Develop logging, tracing, and alerting systems for deployed models and AI agents. Conduct A/B testing and gather user feedback to refine AI behavior. Address model drift and retrain models as necessary. Best Practices & Research Stay updated with the latest advancements in AI, LLMs, and agentic systems. Implement best practices for prompt engineering, reinforcement learning from human feedback (RLHF), and fine-tuning methodologies. Optimize compute costs and infrastructure usage for AI applications. Collaborate with researchers and ML engineers to integrate state-of-the-art AI techniques. Strong knowledge on version control tools like GitHub Qualifications & Skills: Proficiency with LLM frameworks such as Hugging Face Transformers, OpenAI API, or Meta AI models. Strong programming skills in Python and experience with deep learning libraries (PyTorch, TensorFlow, JAX). Experience with cloud platforms (AWS, Azure, GCP) and model deployment tools (Docker, Kubernetes, FastAPI, Ray Serve). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG) techniques. Hands-on experience with monitoring tools such as AgentOps, OpenLIT, Langfuse, and Langtrace. Understanding of prompt engineering, LLM fine-tuning, and agent-based automation. Excellent problem-solving skills and the ability to work in a dynamic AI research and deployment team. Preferred Qualifications: Experience in reinforcement learning, fine-tuning LLMs, or training custom models. Knowledge of security best practices for AI applications. Contributions to open-source AI/ML projects or research publications in the field.

Job description Job description Job Summary: We are looking for a results-driven and innovative Data Scientist with 46 years of experience in data analysis, machine learning, and product optimization. The ideal candidate will have a strong foundation in Python, SQL, and cloud services, along with practical exposure to GenAI, LLMs, and MLOps frameworks. You will be responsible for building scalable data pipelines, developing machine learning models, and solving real-world business problems with data-driven solutions. Key Responsibilities: Design and deploy LLM-powered solutions (e.g., RAG, LangChain, Vector DB) to enhance business processes. Build and fine-tune traditional ML models (Random Forest, Decision Trees) for predictive analytics. Optimize LLM performance using LoRA fine-tuning and post-training quantization. Develop and deploy containerized AI applications using Docker and FastAPI. Collaborate with agents like CrewAI and LangSmith to automate document processing and data extraction workflows. Implement Python & SQL-based ETL pipelines for real-time data ingestion. Design dashboards and KPI monitoring tools using Metabase to enable data-driven decision-making. Create data consumption triggers and automate reporting for international stakeholders. Moderate large-scale live virtual data science classes and provide operational support. Required Skills: Programming: Python, SQL, FastAPI ML & AI: Random Forest, Decision Trees, Clustering, PCA, DL, NLP, Transformers, Gen AI Frameworks/Tools: LangChain, MLflow, Kubeflow, CrewAI, LangSmith DevOps: Docker, Git Databases: MySQL, PostgreSQL, MongoDB Cloud: AWS (S3, EC2) Visualization: Metabase Other: Experience with LLM fine-tuning and quantization Role & responsibilitiesRole & responsibilities Preferred candidate profile

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649