aimlroles

Data Science GenAI Engineer

Fa Ewjt Saasfaprod1 Open · verified Oct 22, 2026
Hybrid Gurugram Full-time Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.

Pay not stated AI Engineering salary

RoleAI Engineering
SeniorityMid-level
LocationGurugram
WorkplaceHybrid
EmploymentFull-time
PostedOct 12, 2026 · 10d ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and launch applications powered by GPT-based or open-source language models
  • Improve prompts, retrieval-augmented generation, and fine-tuning workflows for quality and performance
  • Connect AI models to live systems through APIs, microservices, and cloud platforms
  • Test model outputs, reduce hallucinations, and tune accuracy, safety, and response time
  • Set up monitoring, logs, and feedback cycles while following security, privacy, and responsible AI guidance

What you bring

  • Four to six years in software engineering or machine learning, including at least two years with GenAI, LLMs, or applied NLP
  • Strong Python skills and practical experience with LLM APIs, prompt engineering, RAG, and vector databases
  • Experience deploying AI or ML solutions in a cloud environment and building RAG applications with LangGraph and FastAPI
  • Working knowledge of data structures, APIs, system design, and NLP concepts such as embeddings and transformers

Who this fits

This mid-level role suits an engineer who can build and deploy GenAI applications and work with product managers, data scientists, and backend engineers. The position is hybrid in Gurugram, India.

From the employer

  • 4–6 years of overall software engineering or ML experience.
  • 2+ years of hands-on experience in Generative AI, LLMs, or applied NLP.
  • Strong programming skills in Python (required); experience with JavaScript/TypeScript is a plus.
  • Practical experience with:
    • LLM APIs and frameworks (e.g., OpenAI-compatible APIs, LangChain, LlamaIndex)
    • Prompt engineering and RAG architectures
    • Vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma)
  • Experience deploying ML/AI solutions in cloud environments (AWS, Azure, or GCP).
  • Solid understanding of data structures, APIs, and system design.
  • Ability to write clean, maintainable, and testable code.
  • Design, develop, and deploy Generative AI applications using LLMs (e.g., GPT-based, open-source models).
  • Build and optimize prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning pipelines.
  • Integrate GenAI models into production systems using APIs, microservices, and cloud platforms.
  • Collaborate with product managers, data scientists, and backend engineers to translate business needs into AI-driven solutions.
  • Evaluate model performance, mitigate hallucinations, and improve accuracy, safety, and latency.
  • Implement monitoring, logging, and feedback loops for continuous model improvement.
  • Stay current with emerging GenAI frameworks, tools, and best practices.
  • Ensure compliance with security, privacy, and responsible AI guidelines.
  • Experience in RAG based applications using LangGraph and FastAPI.
  • Familiarity with MLOps practices (CI/CD for ML, model versioning, monitoring).
  • Knowledge of NLP concepts such as embeddings, transformers, and tokenization.