Agentic Systems Engineer in India at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Agentic Systems Engineer based in India.

As an Agentic Systems Engineer, you will help build the next generation of AI-powered applications designed to transform proposal workflows in the architecture, engineering, and construction industry. You will work on systems that reason, use tools, maintain memory, retrieve information, and collaborate with users. The role spans multi-agent orchestration, MCP servers, skills, retrieval, evaluations, observability, and production infrastructure. You will contribute directly to modular, reliable agentic systems while maintaining a strong focus on quality and measurable performance. You will investigate real production behavior through traces and data, turning insights into practical improvements. This is an ideal opportunity for an engineer who enjoys working at the frontier of generative AI and wants meaningful ownership in a fast-moving technical environment.

• Build modular, plug-and-play AI agents that integrate cleanly into a broader agentic application architecture.
• Design and implement memory capabilities, including short-term and long-term memory, summarization, and retrieval-backed context.
• Develop and integrate tools, MCP servers, and reusable agent skills.
• Build reliable production software with strong separation of concerns, maintainable architecture, and meaningful automated tests.
• Own the quality of delivered features through testing, evaluations, monitoring, and observability.
• Analyze production traces, logs, and evaluation results to understand actual system behavior and identify opportunities for improvement.
• Investigate issues systematically, identify root causes, and implement data-driven fixes rather than relying on assumptions.
• Contribute to retrieval systems, agent orchestration, context management, and other components of the agentic technology stack.
• Stay current with emerging agent frameworks, LLM capabilities, and best practices, helping inform technical decisions and future system design.

• 2–4 years of professional experience developing and maintaining production software.
• Strong Python skills, including clean, idiomatic syntax, well-structured modules, object-oriented design, separation of concerns, and effective testing practices.
• Solid understanding of core agentic AI and LLM concepts, including RAG, prompting patterns, tool use, structured outputs, streaming, context management, and generative AI fundamentals.
• Hands-on experience building a non-trivial application or project using modern agentic or LLM tooling.
• Ability to quickly understand and navigate unfamiliar codebases.
• Strong analytical mindset and attention to detail, with a disciplined approach to understanding problems before implementing solutions.
• Data-driven approach to engineering, with the ability to use production traces, evaluation metrics, and logs to identify meaningful signals and guide decisions.
• Hands-on experience with Langfuse, LangSmith, or an equivalent LLM tracing and observability platform.
• Genuine curiosity about emerging AI technologies, agent architectures, frameworks, and industry developments.
• Experience with search and retrieval technologies such as embeddings, vector databases, hybrid retrieval, and reranking is highly valued.
• Experience designing and implementing end-to-end LLM evaluations, including evaluation criteria, measurement frameworks, test harnesses, and maintaining reliable scores as models and prompts evolve, is a strong advantage.
• Deeper experience with LangGraph, including custom graphs, checkpointers, context-management nodes, summarization, windowing, and state pruning, is particularly valuable.
• Strong communication skills and the ability to explain technical decisions, projects, and trade-offs clearly.

• Remote work opportunity based in India.
• Opportunity to work on cutting-edge agentic AI and LLM applications.
• Hands-on exposure to multi-agent orchestration, MCP, memory systems, retrieval, evaluations, and observability.
• High level of ownership and trust from the beginning.
• Fast-moving engineering environment focused on experimentation, measurable outcomes, and continuous learning.
• Opportunity to work on technically challenging problems at the frontier of generative AI.
• Structured and rigorous interview process designed to evaluate technical ability, problem-solving, and cultural alignment.
• Potential for significant professional growth as agentic AI technologies and applications evolve.