We are looking for a hands-on Generative AI Engineer to design, build, and deploy enterprise-grade GenAI platform capabilities across multiple business units.
This role focuses on developing scalable, reusable AI components across the full stack—covering RAG systems, agent orchestration, LLM infrastructure, and GenAIOps—on GCP (primary) and Azure.
This is a core engineering role, not a research or client-facing position.
Key Responsibilities
- Design and build production-ready GenAI systems and platform components
- Develop and deploy RAG pipelines (data ingestion, embeddings, retrieval, APIs)
- Implement agent-based architectures (orchestration, routing, memory, workflows)
- Build and manage LLM infrastructure (model routing, caching, rate limiting, observability)
- Develop scalable APIs and services for AI capabilities
- Implement GenAIOps/MLOps practices (prompt management, evaluation, monitoring, deployment)
- Work with GCP services (Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub) to deploy solutions
- Ensure AI safety, governance, and compliance (PII protection, guardrails, auditability)
- Collaborate with cross-functional teams to deliver reusable, enterprise-grade solutions
Required Skills & Experience
- Strong hands-on experience in Generative AI and RAG systems (production level)
- Experience building multi-agent or agentic AI systems
- Proficiency in Python and backend/API development
- Hands-on experience with GCP AI/ML ecosystem (Vertex AI, BigQuery, etc.)
- Solid understanding of LLM infrastructure and orchestration layers
- Experience with CI/CD pipelines and Infrastructure as Code (Terraform)
- Knowledge of GenAIOps/MLOps practices and model lifecycle management
- Understanding of AI safety, governance, and compliance
Nice to Have
- Experience with LangChain, LlamaIndex, or similar frameworks
- Familiarity with RAG evaluation tools (RAGAS, DeepEval)
- Knowledge of Knowledge Graphs with RAG
- Experience in multi-cloud environments (GCP + Azure)
- Exposure to BFSI/regulated domains
What We’re Looking For
- Engineers who have built and deployed real-world GenAI systems at scale
- Strong backend and systems-thinking mindset
- Ability to work in fast-paced, enterprise environments
Role Type
- Individual Contributor (IC)
- Platform Engineering / Backend-heavy GenAI role
Shubham Vishwakarma
Full Stack Developer - Averlon
About Quantiphi
About
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine and realize transformational opportunities at the heart of the business. Since its inception in 2013, Quantiphi has solved the toughest and most complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve accelerated and quantifiable business results.
Tech stack
NodeJS (Node.js)
PythonCompany video
Candid answers by the company
Bengaluru, Mumbai, and Trivandrum
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