AI/ML Developer

Were seeking a seasoned AI/ML Developer to join our tech team and help build next-generation GenAI products and scalable AI-powered APIs. You’ll architect and deploy intelligent workflows on Google Cloud Platform, integrate cutting-edge LLMs, and design real-time intent-detection systems across multiple user journeys.

Key Responsibilities

• Model Development & Deployment:

• Build, train and deploy AI/ML models using GCP’s ADK and Vertex AI.
  
• Implement prompt-engineering strategies for large language models (e.g., Gemini).
  

• Vector Search & Retrieval:

• Design and maintain vector search pipelines on GCP.
  
• Integrate with LangChain and other tools for context-aware retrieval.
  

• API & Backend Engineering:

• Develop secure, scalable RESTful APIs using FastAPI and Python.
  
• Automate deployments via GitHub CI/CD workflows.
  

• Intent-Detection Systems:

• Architect multi-flow intent-detection pipelines with high accuracy.
  
• Continuously monitor and optimize model performance.
  

• Cloud Infrastructure & Security:

• Enforce best practices for secure, scalable GCP services.
  
• Collaborate with DevOps to ensure reliable, automated infrastructure.
  

• Collaboration & Documentation:

• Work closely with cross-functional teams (DevOps, Product, QA).
  
• Maintain clear technical documentation and share knowledge.
  

Required Skills & Qualifications:

• AI/ML Expertise:

• 4+ years hands-on with AI/ML solutions in production.
  
• Proficiency with GCP services: Vertex AI, ADK, Firestore.
  

• Vector Search & LLM Integration:

• Experience building vector search pipelines on GCP.
  
• Strong familiarity with Gemini, LangChain, or similar LLM frameworks.
  

• Backend Development:

• Advanced Python skills; production experience with FastAPI.
  
• Solid understanding of REST principles, authentication, and security.
  

• DevOps & Automation:

• GitHub Actions (or equivalent) for CI/CD.
  
• Infrastructure as Code (Terraform, Deployment Manager, etc.).
  

• Intent Detection & NLP:

• Track record of building intent-classification or NLU systems.
  
• Familiarity with metrics and A/B testing for conversational AI.
  

• Soft Skills:

• Excellent problem-solving and analytical abilities.
  
• Strong communication skills and a collaborative mindset.