5 Crew Ai Jobs

Role & responsibilities Lead End-to-End ML Projects: Own the full lifecycle of ML solutions from problem scoping, data exploration, model development, deployment, and post-deployment monitoring. Own the Gen AI Strategy: Define and drive the technical vision and execution strategy for Gen AI use cases across the organization. Architect Scalable Solutions: Design robust ML systems and pipelines that integrate seamlessly into production environments. Team Leadership: Mentor and guide a team of ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous learning. Modeling & Research: Stay up to date with the latest advancements in ML/AI and guide experimentation with novel algorithms (e.g., deep learning, NLP, GenAI, reinforcement learning). Build RAG & Prompt Engineering Pipelines: Design scalable architectures for RAG, vector search, prompt tuning, and prompt chaining with tools like LangChain, LlamaIndex, and FAISS. Stakeholder Collaboration: Work closely with product managers, engineers, and domain experts to translate business problems into technical solutions. Operationalize ML: Partner with MLOps/DevOps teams to deploy, monitor, and maintain ML models in production, ensuring reliability and scalability. Preferred candidate profile Bachelors or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (PhD is a plus). 8+ years of hands-on experience in machine learning, with at least 1–2 years in a leadership or mentorship role. Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, HuggingFace Transformers, etc. Strong understanding of statistics, optimization, and model evaluation techniques. Experience with cloud platforms (AWS, GCP, or Azure) and tools like Docker, Kubernetes, MLflow, or Kubeflow. Proficiency in Python and Gen AI frameworks such as LangChain, Crew AI, or similar. Proven track record of deploying ML models into production at scale. Excellent communication and leadership skills.

Key Responsibilities: Agentic AI solution implementation leveraging Azure ecosystem, open-source RPA tools and scripting solutions where needed. Automation Solution Development : Create, deploy, and optimize automation workflows and BOTs using Agentic AI frameworks like Autogen. Leverage AI-driven processes to enable smart automation in business operations. Hands-on Cloud Integration : Design and implement automation solutions that integrate seamlessly with Microsoft Azure services (such as Azure Functions , Logic Apps , Azure Storage ) and other cloud-based tools to improve scalability and performance. AI and Python Libraries : Utilize Agentic AI frameworks for enhancing automation processes, and use Python libraries like Playwright for web automation, browser interaction, and testing. Implement machine learning models or AI algorithms where applicable to automate decision-making and data processing tasks. Scripting & Customization : Develop custom scripts in languages such as Python , PowerShell , JavaScript , and others to extend the functionality of RPA solutions, optimize workflows, and troubleshoot complex scenarios. Stakeholder Engagement : Collaborate with business analysts, IT teams, and key stakeholders to gather requirements, align automation goals with business priorities, and ensure automation solutions meet the desired business outcomes. Process Optimization : Continuously monitor, analyze, and optimize existing automation systems to enhance performance, reduce processing times, and ensure robustness. Identify opportunities to further automate manual processes across departments. Technical Leadership & Mentorship : Provide leadership, mentorship, and training to Agentic AI developers and junior engineers. Share best practices and foster a collaborative environment to ensure high standards of automation development.

Job Overview: We are looking for a highly skilled Gen AI Developer to design, build, and deploy intelligent autonomous systems. This role involves developing AI-powered agents that can perceive, reason, and act independently, leveraging LLMs, reinforcement learning, and multi-agent systems. You will work on cutting-edge AI frameworks like LangChain, AutoGen, CrewAI, and MLOps pipelines for scalable deployment. Key Responsibilities: AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Required Skills & Qualifications: Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills.

Job description Job Title: Software Engineer (SaaS Security) Duration: Full Time Opportunity Location: Remote (India) Note: Need someone who can join immediately OR at least in 30-45 days. Note: Need someone who can join immediately OR at least in 30-45 days. Job Description: Your Impact Responsible for the complete software development life cycle including requirement analysis, design, development, deployment and support. Responsible for developing software products for Agentic AI Security. Write clean, testable, readable, scalable and maintainable Java/ Python / Go lang code. Design, develop and implement highly scalable software features and infrastructure on our security platform ready for cloud native deployment from inception to completion. Participate actively and contribute to design and development discussions. Develop solid understanding and be able to explain advanced Cloud Computing and Cloud Security concepts to others. Work cross-functionally with Product Management, SRE, Software, and Quality Engineering teams to deliver new security as a service offerings to the market in a timely fashion with excellent quality. Be able to clearly communicate goals and desired outcomes to internal project teams. Work closely with customer support teams to improve end-customer outcomes. Your Experience 8+ years of experience in software engineering, with a focus on cloud-native application development, at large organizations or innovative startups. 5+ Experience and deep understanding for building connectors for Low Code / No Code and Agentic AI platforms like Microsoft Copilot Studio, Microsoft Power Platform, Salesforce Agentforce, Zappier, Crew AI, Marketo etc. 8+ Experience building connectors for SaaS Applications like Microsoft O365, Power Apps, Salesforce, ServiceNow etc. Strong programming skills in one of Python, GO, or Java, with experience in building distributed systems. Preferred experience with security products- Data and DLP, CASB Security, SASE, integration with third party APIs and services. 8+ years of Experience with running workloads on cloud-based architectures. (AWS/GCP experience preferred) 8+ years of experience in cloud technologies like Elasticsearch, Redis, Kafka, Mongo DB, Spring Boot. Experience with Docker and Kubernetes or other container orchestration platforms. Excellent troubleshooting abilities. Isolate issues found during testing and verify bug fixes once they are resolved. Experience with backend development (Rest APIs, Databases, Serverless computing) of distributed cloud applications. Experience with building and delivering services and workflows at scale, leveraging microservices architectures. Experience with the agile process and working with software development teams involved with building out full stack products, deployed on the cloud at scale. Good understanding of public cloud design considerations and limitations in areas of microservice architectures, security, global network infrastructure, distributed systems, and load balancing. Strong understanding of principles of DevOps and Continuous Delivery. Can-do attitude and ability to make trade-off judgements with data driven decision making. High energy and the ability to work in a fast-paced environment. Enjoys working with many different teams with strong collaboration and communications skills. Preferred Qualification: BS/MS in Computer Science, other engineering/technical degree

Job Overview: We are looking for a highly skilled AI & Agentic Developer to design, build, and deploy intelligent autonomous systems. This role involves developing AI-powered agents that can perceive, reason, and act independently, leveraging LLMs, reinforcement learning, and multi-agent systems. You will work on cutting-edge AI frameworks like LangChain, AutoGen, CrewAI, and MLOps pipelines for scalable deployment. Key Responsibilities: AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Required Skills & Qualifications: Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills. Preferred Qualifications: Masters. in Computer Science, AI, or Data Science. Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer). Experience with autonomous systems, robotics, or digital twins. 5-7 years of similar or equivalent experience.