Location: Hyderabad, Experience: 7-9 Years Employment Type: Full-time Company Description At Antz AI, we lead the AI revolution with a focus on AI Agentic Solutions. Our mission is to integrate intelligent AI Agents and Human-Centric AI solutions into core business processes, driving innovation, efficiency, and growth. Our consulting is grounded in robust data centralization, resulting in significant boosts in decision-making speed and reductions in operational costs. Through strategic AI initiatives, we empower people to achieve more meaningful and productive work. Role Summary: We are seeking a highly experienced and dynamic Senior AI Consultant with 7-9 years of overall experience to join our rapidly growing team. The ideal candidate will be a hands-on technologist with a proven track record of designing, developing, and deploying robust AI solutions, particularly leveraging agentic frameworks. This role demands a blend of deep technical expertise, strong system design capabilities, and excellent customer-facing skills to deliver impactful real-world products. We are looking for an immediate joiner who can hit the ground running. Key Responsibilities: Solution Design & Architecture: Lead the design and architecture of scalable, high-performance AI solutions, emphasizing agentic frameworks (e.g., Agno, Langgraph) and microservices architectures. Hands-on Development: Develop, implement, and optimize AI models, agents, and supporting infrastructure. Write clean, efficient, and well-documented code, adhering to software engineering best practices. Deployment & Operations: Oversee the deployment of AI solutions into production environments, primarily utilizing AWS services. Implement and maintain CI/CD pipelines to ensure seamless and reliable deployments. System Integration: Integrate AI solutions with existing enterprise systems and data sources, ensuring robust data flow and interoperability. Customer Engagement: Act as a key technical liaison with clients, understanding their business challenges, proposing AI-driven solutions, and presenting technical concepts clearly and concisely. Best Practices & Quality: Champion and enforce best practices in coding, testing, security, and MLOps to ensure the delivery of high-quality, maintainable, and scalable solutions. Problem Solving: Diagnose and resolve complex technical issues related to AI model performance, infrastructure, and integration. Mentorship: Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and excellence. Required Qualifications: Experience: 7-9 years of overall experience in software development, AI engineering, or machine learning, with a strong focus on deploying production-grade solutions. Agentic Frameworks: Demonstrated hands-on experience with agentic frameworks such as Langchain, Langgraph, Agno, AutoGen , or similar, for building complex AI workflows and autonomous agents. Microservices Architecture: Extensive experience in designing, developing, and deploying solutions based on microservices architectures. Cloud Platforms: Proven expertise in AWS services relevant to AI/ML and microservices (e.g., EC2, S3, Lambda, ECS/EKS, SageMaker, DynamoDB, API Gateway, SQS/SNS). Programming & MLOps: Strong proficiency in Python. Experience with MLOps practices, including model versioning, monitoring, and pipeline automation. System Design: Excellent understanding and practical experience in system design principles, scalability, reliability, and security. Real-World Deployment: A strong portfolio demonstrating successful deployment of AI products or solutions in real-world, production environments. Customer-Facing: Prior experience in customer-facing roles, with the ability to articulate complex technical concepts to non-technical stakeholders and gather requirements effectively. Immediate Availability: Ability to join immediately. Preferred Qualifications / Bonus Points: Experience with other cloud platforms (Azure, GCP). Knowledge of containerization technologies (Docker, Kubernetes). Familiarity with various machine learning domains (NLP, Computer Vision, Generative AI). Contributions to open-source AI projects.