Artificial Intelligence Engineer

6 years

0 Lacs

Posted:12 hours ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Ekyam.ai: Integrating Systems, Unleashing Intelligence - Join Our India Expansion!

Are you ready to solve complex integration challenges and build the next generation of AI-driven retail technology? Ekyam.ai, headquartered in New York, US, is expanding globally and establishing its new team in India! We are looking for talented individuals like you to be foundational members of our Indian presence.

Ekyam.ai is developing a groundbreaking AI-native middleware platform that connects disparate retail systems (ERP, OMS, WMS, POS, etc.) and creates a unified, real-time, vectorized data layer. We enable intelligent automation and transform how retailers leverage their data by integrating cutting-edge AI capabilities.


Role

AI Developer

customizing and deploying LLMs in-house


Key Responsibilities

  • AI Agent Development:

     Design, develop, test, and maintain the core logic for 

    AI Agents

     within 

    FastAPI

     services. Orchestrate agent tasks, manage state, interact with platform data/workflows, and integrate LLM capabilities.
  • LLM API Integration & Prompt Engineering:

     Integrate with external 

    LLM provider APIs

    . Design, implement, and rigorously test effective 

    prompts

     for diverse retail-specific tasks (generation, Q&A, summarization).
  • RAG Implementation:

     Implement and optimize 

    Retrieval-Augmented Generation (RAG)

     patterns using 

    vector databases

     to provide relevant context to LLM API calls made by agents.
  • FastAPI Microservice Development:

     Build and maintain the scalable 

    FastAPI

     microservices that host AI Agent logic and handle interactions with LLMs and other platform components in a containerized environment (

    Docker, Kubernetes

    ).
  • Data Processing for AI:

     Prepare and preprocess data required for effective prompt context, RAG retrieval, and potentially for future fine-tuning tasks.
  • Collaboration & Future Adaptation:

     Work with cross-functional teams to deliver AI features. Stay updated on LLM advancements and be prepared to learn and contribute to potential future in-house LLM fine-tuning and deployment efforts.


Required Skills & Qualifications

  • 3–6 years

     of hands-on experience in software development with a strong focus on 

    AI/ML application development

    .
  • Demonstrable experience 

    integrating and utilizing external LLM APIs

     (e.g., OpenAI, Anthropic, Google) in applications.
  • Proven experience with 

    Prompt Engineering

     techniques.
  • Strong 

    Python

     programming skills.
  • Practical experience building and deploying 

    RESTful APIs

     using 

    FastAPI

    .
  • Experience designing and implementing application logic for 

    AI-driven features or agents

    .
  • Understanding and practical experience with 

    RAG

     concepts and 

    vector databases

     (Pinecone, FAISS, etc.).
  • Solid understanding of core 

    Machine Learning concepts

     and familiarity with frameworks like 

    PyTorch, TensorFlow, or Hugging Face

     (important for understanding models and future adaptation).
  • Familiarity with 

    cloud platforms

     (

    AWS, GCP, or Azure

    ) and containerization (

    Docker, Kubernetes

    ) for application deployment.
  • Solid problem-solving skills and clear communication abilities.
  • Experience working effectively in an 

    agile

     environment.
  • Willingness and capacity to learn and adapt

     towards future work involving deeper LLM customization and deployment.
  • Bachelor's or Master's degree in Computer Science, AI, or a related field.
  • Ability to work independently and collaborate effectively in a remote setting.


Preferred Qualifications

  • Experience with frameworks like 

    LangChain

     or LlamaIndex.
  • Experience with observability and debugging tools for LLM applications, such as

    LangSmith.

  • Experience with graph databases (e.g., Neo4j) and query languages (e.g., Cypher).
  • Experience with 

    MLOps

     practices, applicable to both current application monitoring and future model lifecycle management.
  • Experience optimizing API call performance (latency/cost) or model inference.
  • Knowledge of 

    AI security

     considerations and 

    bias mitigation

    .


Why Join Ekyam.ai?

Be a foundational member of our new India team! This role offers a unique blend: build intelligent AI Agents leveraging cutting-edge external LLMs today, while positioning yourself at the forefront of our future plans for deeper AI customization. You'll gain expertise across the AI application stack (APIs, RAG, Agents, potential future MLOps) and collaborate within a vibrant global team shaping the future of AI in e-commerce. We offer competitive compensation that values your current skills and growth potential.

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