Posted on: 21/05/2026
Position : AI & ML Tech Lead
Job Location : Indore, MP
Job Type : Full Time
Experience Level : 6- 10 Years
Required Skills :
Data Scientist, MCP, Agentic AI, LLM understanding, RAG. Architecture end to end, built systems which run in productions.
We are seeking a highly skilled AI/ML Leader with a strong foundation in Python/Java and microservices architecture, who can bridge the gap between traditional backend systems and modern AI/ML platforms.
The ideal candidate will have experience or a strong interest in LLM-based frameworks (e.g., LangChain, Agentic AI), and be capable of designing scalable, intelligent solutions that integrate with major AI platforms.
Key Responsibilities :
- Architect and design scalable, secure, and high-performance microservices using Python OR Java.
- Collaborate with AI/ML teams to integrate LLM-based tools and frameworks into enterprise applications.
- Understand and work with MCP (Model Context Protocol), A2A (Agent-to-Agent) communication, and LLM orchestration frameworks like LangChain and Agentic AI.
- Evaluate and recommend AI platforms and tools for enterprise use cases.
- Translate business requirements into technical solutions that leverage both traditional and AI-driven
components.
- Lead technical discussions with stakeholders, including product managers, data scientists, and platform teams.
- Ensure architectural alignment with enterprise standards and best practices.
Required Skills & Experience :
- 6+ years of experience in backend development with Python/Java
- Proven experience designing and deploying microservices architectures.
- Familiarity with AI/ML concepts, especially LLMs, prompt engineering, and AI agents.
- Understanding of LangChain, Agentic AI, or similar LLM orchestration frameworks.
- Experience integrating with AI platforms (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face).
- Strong understanding of API design, event-driven systems, and cloud-native architectures.
- Excellent communication and stakeholder management skills.
- Hands-on experience with LLM-based applications or AI agent frameworks.
- Exposure to MCP, A2A, or similar AI infrastructure concepts.
- Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.
- Knowledge of data pipelines and AI model lifecycle management
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