200000 - 500000 Indian Rupee - Yearly
Bangalore, Karnataka, India
Information Technology
Full-Time
SourcingXPress
Overview
Company: Xzayogn
Website: Visit Website
Business Type: Startup
Company Type: Product
Business Model: B2B
Funding Stage: Pre-seed
Industry: Consumertech
Salary Range: ₹ 2-5 Lacs PA
Job Description
Job Summary:
We are seeking an AI Engineer who is an expert in agentic AI—designing autonomous, goal-oriented systems capable of reasoning, planning, and executing tasks. The ideal candidate will have extensive experience with Model Context Protocol (MCP), LangChain, and LangGraph, along with proficiency in Python and Go (Golang). This role will focus on building advanced AI agents that leverage external tools, maintain stateful workflows, and deliver measurable outcomes in real-world applications.
Key Responsibilities
Website: Visit Website
Business Type: Startup
Company Type: Product
Business Model: B2B
Funding Stage: Pre-seed
Industry: Consumertech
Salary Range: ₹ 2-5 Lacs PA
Job Description
Job Summary:
We are seeking an AI Engineer who is an expert in agentic AI—designing autonomous, goal-oriented systems capable of reasoning, planning, and executing tasks. The ideal candidate will have extensive experience with Model Context Protocol (MCP), LangChain, and LangGraph, along with proficiency in Python and Go (Golang). This role will focus on building advanced AI agents that leverage external tools, maintain stateful workflows, and deliver measurable outcomes in real-world applications.
Key Responsibilities
- Architect and develop agentic AI systems that autonomously perform multi-step tasks, leveraging reasoning, decision-making, and tool integration.
- Utilize LangChain and LangGraph to design stateful, multi-agent workflows with persistence, memory, and cyclic execution capabilities.
- Implement Model Context Protocol (MCP) to connect AI agents with external tools, APIs, and data sources, enabling dynamic, context-aware behavior.
- Write high-quality Python code to build, train, and deploy agentic AI models, integrating libraries like Hugging Face, PyTorch, or custom LLM frameworks.
- Develop scalable backend services in Go (Golang) to support agentic AI infrastructure, including low-latency APIs and microservices.
- Optimize agents for performance, adaptability, and reliability, ensuring they meet user-defined goals efficiently.
- Collaborate with product and engineering teams to translate business requirements into agentic AI solutions.
- Experiment with cutting-edge techniques in autonomous AI, such as reinforcement learning, planning algorithms, or human-in-the-loop validation.
- Monitor and refine agent behavior using observability tools and metrics to ensure alignment with objectives.
- Bachelor’s or Master’s degree in Computer Science, AI, Engineering, or a related field (or equivalent experience).
- 4+ years of experience in AI engineering, with a specialized focus on agentic AI systems.
- Deep understanding of agentic AI principles, including autonomy, goal-directed behavior, and multi-agent coordination.
- Hands-on expertise with LangChain and LangGraph for orchestrating agentic workflows with state management and tool integration.
- Proven experience implementing Model Context Protocol (MCP) to enable AI agents to interact with external systems.
- Advanced proficiency in Python for AI development, including experience with LLMs, NLP, or reinforcement learning frameworks.
- Strong skills in Go (Golang) for building scalable, concurrent backend systems to support AI deployments.
- Familiarity with graph-based architectures, memory contexts, and agent persistence mechanisms.
- Excellent problem-solving skills and ability to work in a fast-paced, innovative environment.
- Experience deploying agentic AI systems in production (e.g., AWS, GCP, Azure) using containerization (Docker, Kubernetes).
- Background in designing agents for specific domains (e.g., job automation, customer support, or decision-making).
- Knowledge of advanced AI techniques like multi-agent reinforcement learning, symbolic reasoning, or planning under uncertainty.
- Contributions to open-source projects in agentic AI, LangChain, LangGraph, or MCP.
- Familiarity with observability tools (e.g., LangSmith) for debugging and evaluating agent performance.
- Languages: Python, Go (Golang)
- Frameworks: LangChain, LangGraph, MCP
- Expertise: Agentic AI, autonomous systems, LLM orchestration
- Tools: Git, Docker, RESTful APIs, observability platforms
- Concepts: Multi-agent systems, goal-driven AI, stateful workflows, tool integration
- Soft Skills: Analytical thinking, collaboration, adaptability
- Lead the development of next-generation agentic AI systems with real-world impact.
- Work with a team of AI pioneers in a dynamic, innovative environment.
- Competitive compensation, equity, and benefits package.
- Opportunities for growth and ownership of cutting-edge projects.
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