Applied AI / LLM Engineer

About Us:

Agentic AI

Role Overview:

Applied AI / LLM Engineer

Key Responsibilities:

• Design and implement AI pipelines using

  LLMs

  ,

  LangChain

  , and

  vector databases

  (e.g., FAISS, Qdrant, Pinecone).
• Develop and deploy

  speech-to-text

  and

  text-to-speech

  flows integrated with AI agents.
• Fine-tune and evaluate language models for domain-specific needs.
• Create

  multi-channel communication agents

  using email, SMS, WhatsApp, and voice.
• Structure unstructured data inputs and manage embeddings for search and reasoning.
• Integrate AI agents into

  Worc workflows

  using Python and RESTful APIs.
• Collaborate with product teams to define user journeys and recommend AI integration points.
• Optimize pipelines for latency, accuracy, and cost-efficiency.
• Contribute to internal best practices, reusable components, and documentation.

Required Skills:

• Strong programming skills in

  Python

  .
• Hands-on experience with

  LLM frameworks

  like

  LangChain

  ,

  Transformers

  , or

  LlamaIndex

  .
• Experience working with

  vector databases

  (e.g., FAISS, Qdrant, Weaviate, Pinecone).
• Understanding of

  prompt engineering

  ,

  RAG (retrieval-augmented generation)

  , and

  embedding models

  .
• Knowledge of

  fine-tuning LLMs

  , transfer learning, and model optimization.
• Familiarity with

  speech-to-text

  (e.g., Whisper, Google STT) and

  text-to-speech

  (e.g., ElevenLabs, AWS Polly) APIs.
• API integration and building scalable microservices using Python (FastAPI or Flask preferred).
• Strong problem-solving and experimentation mindset.

Preferred Skills:

• Experience working with platforms like

  UIPath

  ,

  n8n

  , or

  Make

  .
• Exposure to deploying models using cloud GPU environments (e.g., GCP, AWS, Azure, Nvidia).
• Familiarity with basic

  DevOps

  ,

  Docker

  , and

  CI/CD

  practices.

What We Offer:

• A front-row seat in building the future of agentic automation.
• Flexible work environment with high ownership and creative freedom.
• Competitive salary with performance-based bonuses.
• Equity options for long-term contributors.
• Opportunity to work on cutting-edge technologies in AI and automation.
• Culture of innovation, continuous learning, and supportive collaboration.