AI-ML Engineer

Experience: 3 years to 5 Years
Category: zINACTIVE - Information Technology Main location: Bangalore Employment Type: Full Time Job Description: - AI-ML Engineer We are seeking a high-impact AI/ML Software Engineer to join our AI engineering team. The ideal candidate brings deep expertise in modern agentic frameworks such as Google ADK, CrewAI, AutoGen, or LangGraph, and hands-on experience in developing Model Context Protocols (MCP). This role is ideal for individuals passionate about engineering through automation, scaling AI architecture, and contributing to the next generation of agent-based systems. You will work closely with our CICD platform tooling and global architecture teams to enhance and productize our agentic SDLC platform. Key Responsibilities: Design, develop, and maintain Kubernetes-based containerized microservices and CICD automation pipelines that support SDLC. Build modular agent workflows capable of reasoning, collaborating, and adapting dynamically to context and goals. Develop and manage multi-agent systems using frameworks like Google ADK, CrewAI, or AutoGen. Build and optimize MCP pipelines, including context injection, memory caching, semantic retrieval, and embedding-based context scoping. Develop CLIs and SDKs to support MCP testing and integration. Collaborate with cross-functional teams including product, data analytics, and infrastructure to evolve tooling for agent development, prompt evaluation, and telemetry analysis. Fine-tune foundation models (e.g., GPT, Claude, Falcon) for enhanced domain-specific performance. Required Qualifications: Bachelors degree in computer science, Engineering, Mathematics, or a related technical field. 25 years of software engineering experience, with at least 2 years focused on AI/ML or developer platform teams. Strong coding skills in Python and Golang, with a track record of writing clean, secure, and scalable code. Proven experience in MCP implementation, ensuring efficient, coherent, and context-aware data flow in multi-agent LLM systems. Experience with Kubernetes, service mesh technologies (e.g., Istio), and Infrastructure-as-Code (IaC). Familiarity with distributed task orchestration and real-time agent execution environments.