10 Crew Ai Jobs

We are urgently looking for a Senior AI/ML Engineer (C2H) based in Bangalore for on-site work. 7+years Key Requirements: - Proficiency in Prompt Engineering and its strategies - Understanding of LLM functionality and its hyperparameters (temperature, top_p) - Experience with Agentic AI frameworks such as Langchain, Lang graph, and Crew AI - Familiarity with RAG - Skilled in LLM evaluation and observability - Strong command of Python - Ability to deploy on any one of the cloud services If you meet these requirements, we would like to hear from you. [HIDDEN TEXT] hashtag#immediatejoiners hashtag#AI hashtag#PYTHON hashtag#Machinelearning hashtag#banglore Show more Show less

We are looking for a highly skilled and experienced Senior AI Engineer to take charge of designing, developing, and implementing cutting-edge AI systems. Your role will involve working on advanced machine learning models, natural language processing, computer vision, and AI infrastructure to address real-world challenges and foster innovation across our products and services. As a Senior AI Engineer, your key responsibilities will include designing, developing, and deploying scalable AI/ML models for production environments. You will lead end-to-end AI project lifecycles, starting from data collection and preprocessing to model training, evaluation, and deployment. Collaboration with cross-functional teams comprising data scientists, software engineers, and product managers will be essential. Moreover, you will be tasked with optimizing model performance to ensure robustness, fairness, and explainability, while staying abreast of the latest AI and machine learning research and advancements. Mentoring junior engineers and contributing to the establishment of a robust AI engineering culture will also be part of your role. The ideal candidate should possess a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (PhD preferred) along with a minimum of 5 years of experience in AI/ML engineering, showcasing a strong portfolio of deployed models. Proficiency in Python and ML libraries like TensorFlow, PyTorch, Scikit-learn, etc., as well as experience with cloud platforms (AWS, Azure) and MLOps tools are required. A solid grasp of data structures, algorithms, and software engineering principles is crucial, along with excellent problem-solving and communication skills. Preferred qualifications for this role include experience with LLMs, RAG, or agentic AI (Crew AI) systems, familiarity with vector databases, prompt engineering, and AI safety practices, contributions to open-source AI projects or published research papers, and experience with real-time inference systems and edge AI.,

Organization: At CommBank, we never lose sight of the role we play in other peoples financial wellbeing. Our focus is to help people and businesses move forward to progress. To make the right financial decisions and achieve their dreams, targets, and aspirations. Regardless of where you work within our organisation, your initiative, talent, ideas, and energy all contribute to the impact that we can make with our work. Together we can achieve great things. Job Title: Principal Software Engineer - Gen AI Location: Manyata Tech Park, Bangalore Business & Team: CTO- Cloud Modernisation Impact &contribution: As an experienced Principal Engineer who act as thought & technology leader, responsible for providing technical strategy and guidance, overseeing engineering projects of all kinds includes AWS, Cloud Adoption, end to end application design and understanding at enterprise level and good in domain understanding with proven expertise in Gen AI platform engineering and a passion for providing AI-driven solutions, youre ahead of trends and work at the forefront of AI. Roles & responsibilities: Evangelist, leader and champion of strategic practice development across the Gen AI domain. Leader amongst engineers with respected technical views. Lead and direct multiple teams on complex troubleshooting activity. Play a mentoring role in providing design and technical assistance to other members of the team. Utilises an outstanding competency in core business and technical strategies across platforms to deliver best business outcomes. Build Gen AI capability among engineers including but not limited to Knowledge Engineering/prompt engineering/platform engineering. Knowledge Engineering: identifying and gathering relevant domain specific knowledge from various sources and structuring it in a structured way for LLM model to understand and utilize. Platform engineering: Collaborate with other teams to integrate AI solutions into existing workflows and systems to get the platform running and available. They configure and manage the underlying infrastructure that supports the platform, ensuring scalability, reliability, and high availability. Staying up to date on advancements: The field of generative AI is constantly evolving, so staying informed about the latest research and developments, latest releases on different models and their performances are crucial. Ability to develop, suggest best practices of designing infrastructures that support fine-tuning of models to improve performance and efficiency, and troubleshoot any issues that arise during development or deployment. Analyse systems and applications and provide recommendations for design, enhancement and development, and play an active part in their execution. Have a great understanding of software delivery practices and lifecycles in Agile methodologies Essential skills: 16+ years of experience in relevant filed. Strong programming skills in languages (Python/ Java/ C#/ .NET Core) Hands-on experience with cloud platforms (Azure or AWS) and deploying AI models in cloud-native environments. Proven experience in building applications using LLMs and GenAI technologies. Experience with DevOps practices and tools for continuous integration and deployment. Experience with large language models (LLMs) and retrieval-augmented generation (RAG) techniques. Proficiency in using LLM frameworks and toolkits in one or more such as Langchain, Crew AI, MCP, Cline, Aider, and similar technologies. Excellent problem-solving skills and the ability to work in a fast-paced environment. Strong communication and collaboration skills. Education Qualification: Bachelors degree or Masters degree in Engineering in Computer Science/Information Technology. If you&aposre already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you&aposll need to apply through Sidekick to submit a valid application. Were keen to support you with the next step in your career. We&aposre aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696. Advertising End Date: 16/08/2025 Show more Show less

Crew AI Engineer Remote Contractual-6 months Job Description : We are looking for people with strong python skills, knowledge of multi agent frameworks like Crew AI, knowledge of RAG concepts mandatory. Good conceptual knowledge of LLM concepts Langraph and Langchain Required Skills : 5-8 years of experience in AI/ML or automation engineering. Strong hands-on experience with CrewAI or other LLM orchestration frameworks like LangChain, AutoGen, or Semantic Kernel. Proficiency in Python, including experience with async programming and API integration. Deep understanding of LLMs (OpenAI, Anthropic, Mistral, etc.) and prompt engineering. Familiarity with vector databases (e.g., Pinecone, FAISS, Chroma) and embeddings. Experience building and deploying production-ready agent-based solutions. Strong problem-solving skills and ability to translate business requirements into technical implementations.

As a skilled AI expert, you will be responsible for partnering with Product Managers, Engineers, and other key stakeholders to deeply understand business requirements and translate them into actionable technical roadmaps. You will identify and prioritize AI use cases aligned with organizational goals, develop a scalable and sustainable implementation roadmap, and conduct ROI analysis for on-prem LLM deployments. Your role will involve creating sophisticated software designs driven by AI-powered experiences, focusing on performance, scalability, security, reliability, and ease of maintenance. You will define and develop complex enterprise applications through AI Agentic frameworks, ensuring responsiveness, responsibility, traceability, and reasoning. Utilizing modeling techniques like UML and Domain-Driven Design, you will visualize intricate relationships between components and ensure seamless integrations. Leading large-scale platform projects, you will deliver No-code workflow management, HRMS, Collaboration, Search engine, Document Management, and other services for employees. Championing automated testing, continuous integration/delivery pipelines, MLOps, and agile methodologies across multiple teams will also be a key aspect of your role. To excel in this position, you should hold a BTech/MTech/PhD in Computer Sciences with specialization in AI/ML. A proven track record of leading large-scale digital transformation projects is required, along with a minimum of 3+ years of hands-on experience in building AI-based applications using Agentic frameworks. With a minimum of 12-14 years of experience in software design & development, you should have expertise in designing and developing applications and workflows using the ACE framework. Your skillset should include hands-on experience in developing AI Agents based on heterogenous frameworks such as LangGraph, AutoGen, Crew AI, and others. You should also be proficient in selecting and fine-tuning LLMs for enterprise needs and designing efficient inference pipelines for system integration. Expertise in Python programming, developing agents/tools in an AI Agentic framework, and building data pipelines for structured and unstructured data is essential. Additionally, experience in leveraging technologies like RAG (Retrieval Augmented Generation), vector databases, and other tools to enhance AI models is crucial. Your ability to quickly learn and adapt to the changing technology landscape, combined with past experience in the .NET Core ecosystem and front-end development featuring Angular/React/Javascript/Html/Css, will be beneficial. Hands-on experience managing full-stack web applications built upon Graph/RESTful APIs/microservice-oriented architectures and familiarity with large-scale data ecosystems is also required. Additionally, you should be skilled in platform telemetry capture, ingestion, and intelligence derivation, with a track record of effectively mentoring peers and maintaining exceptional attention to detail throughout the SDLC. Excellent verbal and written communication abilities, as well as outstanding presentation and public speaking talents, are necessary to excel in this role. Please note: Beware of recruitment scams.,

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.