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LLM & Multi-Agent Systems Architect Job Opening In India, India – Now Hiring Statsby Solutions


Job description

Job Title: Agentic AI Developer

We’re looking for an AI Engineer who can design, develop, and operationalize agentic AI systems leveraging large language models (LLMs), multi-agent orchestration, and knowledge-graph-driven reasoning.

You’ll work on projects that combine data engineering, automation, and AI reasoning, building production-ready systems that go beyond prompt-based use cases.

Key Responsibilities

  • Design and implement multi-agent architectures that enable goal-driven task orchestration and reasoning using frameworks like LangChain, CrewAI, or Bedrock AgentCore.
  • Build and fine-tune LLM-based agents for tasks such as document understanding, information retrieval, knowledge graph enrichment, and workflow automation.
  • Develop end-to-end pipelines that integrate retrieval-augmented generation (RAG), vector databases, and LLM APIs (e.G., OpenAI, Claude, Gemini, Bedrock).
  • Collaborate with data engineers to align AI agents with structured and unstructured data sources (Snowflake, Databricks, Neo4j, Postgres, etc.).
  • Implement agent memory, context windows, and state management strategies for persistent multi-turn reasoning.
  • Contribute to Statsby’s internal AI accelerators and frameworks for reusable agentic components and observability.
  • Work closely with domain experts in healthcare to embed compliance, auditability, and explainability into AI solutions.

Preferred Skills & Experience

  • Strong programming expertise in Python (FastAPI, LangChain, LlamaIndex, Pydantic, asyncio).
  • Experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock, Vertex AI) and vector databases (Pinecone, Weaviate, Chroma, FAISS).
  • Familiarity with multi-agent frameworks (CrewAI, AutoGen, Bedrock AgentCore, LangGraph).
  • Solid understanding of retrieval pipelines, prompt engineering, and evaluation frameworks (Ragas, TruLens, Evals).
  • Experience integrating AI agents with data platforms (Databricks, Snowflake, AWS S3, Postgres, Neo4j).
  • Knowledge of workflow orchestration (Airflow, ECS, Step Functions, MWAA) is a plus.
  • Experience in regulated industries (Healthcare / Life Sciences) is a strong advantage.


Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your LLM Multi Potential: Insight & Career Growth Guide


Real-time LLM Multi Jobs Trends (Graphical Representation)

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Statsby Solutions adheres to the cultural norms as outlined by Expertini.

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7. Obeying India laws and regulations

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Statsby Solutions interview tips for LLM & Multi Agent Systems Architect

Here are some tips to help you prepare for and ace your LLM & Multi Agent Systems Architect job interview:

Before the Interview:

Research: Learn about the Statsby Solutions's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

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Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your LLM & Multi Agent Systems Architect interview at Statsby Solutions, research the company, understand the job requirements, and practice common interview questions.

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By following these tips, you can increase your chances of making a positive impression and landing the job!

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