We are seeking experienced Data Scientists / AI Engineers to design, build, and deploy production-grade AI and Generative AI solutions. The role requires expertise in Machine Learning, Deep Learning, NLP, and GenAI engineering (RAG, agent-based systems) along with hands-on cloud deployment and MLOps experience.
Open Positions
Location: Hyderabad
Key Responsibilities
Develop ML/DL models for real-world business problems
Build NLP solutions (semantic search, entity recognition, text generation)
Design and implement RAG systems and agent-based AI workflows
Build LLM-powered enterprise applications
Architect end-to-end AI/GenAI solutions
Implement MLOps pipelines (CI/CD, monitoring, governance)
Deploy solutions on GCP and has good experience in vertex AI
Use Docker and Kubernetes for scalable deployments
Collaborate with stakeholders and mentor junior team members
Mandatory Skills
Machine Learning & Deep Learning (hands-on)
Strong Python development
NLP: semantic search, entity recognition, text generation
Generative AI: RAG, Agentic workflows,
LangChain / LangGraph
AI architecture & production deployment
MLOps / AIOps practices
Cloud platforms: GCP
Containerization: Docker, Kubernetes
AI governance and stakeholder management
Additional Expectations
812 Years: Architecture ownership, leadership, Solution Architect, Robust knowledge around GCP Vertex AI, and GenAI concepts building end to end application
4–7 Years: Robust hands-on development and deployment experience. Strong knowledge around GCP Vertex AI, and GenAI concepts building end to end application
Valuable to Have
Vector Databases (Pinecone, FAISS, Azure AI Search)
AI observability and evaluation frameworks
Cost optimization for GenAI systems and token optimization techniques
What We Are Looking For
Candidates with production-grade AI/GenAI experience
Strong engineering mindset with deployment focus
Ability to build scalable, enterprise-ready AI solutions