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Marktine Technology Solutions Pvt. Ltd. · Jaipur, Rajasthan

AI / GenAI Software Engineer (Junior / Associate)

entry_levelfull timePosted 7 days ago
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Stack mentioned

generative-aillmragagentic-aianthropiccopilotvector-databasesopenaigeminifastapipythonlangchainllamaindexrest-apigitqdrantpineconegithubdockerlinux

Job Information

- Date Opened 09/04/2026

- Job Type Full time

- Industry Technology

- Work Experience 10+ Years

- City jaipur

- State/Province Rajasthan

- Country India

- Zip/Postal Code 302015

Job Description

About the Role

We are seeking an execution-focused AI Software Engineer to build and ship production LLM applications, RAG pipelines, and agentic workflows. We want a developer whose daily workflow is already supercharged by AI-assisted coding tools (Claude Code, Cursor, Copilot) to build, test, and ship clean software fast.

What You’ll Do

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Build, optimize, and maintain end-to-end RAG pipelines (document ingestion, chunking, embeddings, vector indexing, retrieval, and reranking).

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Integrate LLM APIs (Anthropic Claude, OpenAI, Gemini, open-source models) into scalable backend services using FastAPI or Python.

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Use AI-native coding setups (Claude Code CLI, Cursor, GitHub Copilot) to explore codebases, write unit tests, and accelerate deployment cycles.

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Design structured outputs, function/tool calling, and agent workflows using frameworks like LangChain, LlamaIndex, or native SDKs.

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Implement basic evals, guardrails, and logging to reduce hallucinations, measure retrieval quality, and monitor API costs.

Benefits

Core Requirements

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Programming: Solid foundation in Python (async, REST APIs, clean object-oriented code) and Git.

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GenAI & RAG: Hands-on experience with vector databases (e.g., Chroma, Qdrant, Pinecone, or pgvector) and embedding models.

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AI Tooling Native: Daily, active user of CLI or IDE agentic coding tools (Claude Code, Cursor, or similar)—you know how to guide AI agents and rigorously inspect generated code.

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Proof of Work: At least 1 shipped or working project beyond basic chat (e.g., semantic search tool, custom RAG on documents, automated agent, or GitHub repo).

Good to Have

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Familiarity with Docker, Linux environment, and basic cloud deployment (AWS/GCP).

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Experience with Model Context Protocol (MCP) or multi-agent orchestration frameworks.

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Exposure to front-end integration (Streamlit, Next.js, or React basics).

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