AI / GenAI Software Engineer (Junior / Associate)

Marktine; Hinoba-an; On-site; PHP 400,000 - 700,000; Full time

Benefits offered by this job

Docker experience

Linux environment

Cloud deployment (AWS/GCP)

Job summary

Marktine Technology Solutions Pvt ltd is hiring an AI / GenAI Software Engineer (Junior / Associate) to build production LLM applications and RAG pipelines. You will integrate multiple LLM APIs, work with vector stores, and drive AI-native coding practices to ship reliable software.

You will collaborate on developing agent workflows, and implement guardrails, tests, and logging to monitor quality and cost. The role emphasizes hands-on coding and rapid delivery in a modern AI-enabled stack.

Qualifications

• Solid foundation in Python with async, REST APIs, and clean OO code.
• Hands-on experience with vector databases and embedding models.
• Daily use of CLI or IDE tools to guide AI agents and inspect code.
• At least one shipped or working project beyond basic chat.

Responsibilities

• Build, optimize, and maintain end-to-end RAG pipelines with ingestion, embeddings, indexing, retrieval, and reranking.
• Integrate LLM APIs into scalable backend services using Python/FastAPI.
• Leverage AI-native coding setups to explore codebases and speed deployments.
• Design structured outputs, tool calling, and agent workflows with LangChain or similar.
• Implement basic evals, guardrails, and logging to reduce hallucinations and manage costs.

Skills

Python programming

REST APIs

Async code

Object-oriented design

Git

Vector databases

Embeddings

AI tooling usage

Tools

Docker

Linux

AWS

GCP

Job description

Marktine Technology Solutions Pvt ltd | Full time

AI / GenAI Software Engineer (Junior / Associate)

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

• Build, optimize, and maintain end-to-end RAG pipelines (document ingestion, chunking, embeddings, vector indexing, retrieval, and reranking).
  
• Integrate LLM APIs (Anthropic Claude, OpenAI, Gemini, open-source models) into scalable backend services using FastAPI or Python.
  
• Use AI-native coding setups (Claude Code CLI, Cursor, GitHub Copilot) to explore codebases, write unit tests, and accelerate deployment cycles.
  
• Design structured outputs, function/tool calling, and agent workflows using frameworks like LangChain, LlamaIndex, or native SDKs.
  
• Implement basic evals, guardrails, and logging to reduce hallucinations, measure retrieval quality, and monitor API costs.
  

Core Requirements

• Programming: Solid foundation in Python (async, REST APIs, clean object-oriented code) and Git.
  
• GenAI & RAG: Hands-on experience with vector databases (e.g., Chroma, Qdrant, Pinecone, or pgvector) and embedding models.
  
• 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.
  
• 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

• Familiarity with Docker, Linux environment, and basic cloud deployment (AWS/GCP).
  
• Experience with Model Context Protocol (MCP) or multi-agent orchestration frameworks.
  
• Exposure to front-end integration (Streamlit, Next.js, or React basics).