Machine Learning (ML)We are looking for a hands-on Associate / Architect – Generative AI to design, build, and deploy enterprise-grade GenAI platform capabilities across multiple business units. This role focuses on developing scalable and reusable AI components across the full stack, covering RAG systems, agent orchestration, LLM infrastructure, and GenAIOps on GCP (primary) and Azure.
Key Responsibilities
- Design and build production-ready Generative AI systems and platform components
- Develop and deploy scalable RAG pipelines including data ingestion, embeddings, retrieval, and APIs
- Build agentic AI systems with orchestration, routing, memory, and workflow management
- Develop and manage LLM infrastructure including model routing, caching, observability, and rate limiting
- Build scalable backend services and APIs for AI-driven applications
- Implement GenAIOps/MLOps practices including prompt management, evaluation, monitoring, and deployment
- Work extensively with GCP services such as Vertex AI, BigQuery, Cloud Run, GKE, and Pub/Sub
- Ensure AI governance, safety, compliance, PII protection, and auditability standards are maintained
- Design scalable enterprise AI architectures with strong focus on performance, reliability, and reusability
- Collaborate with cross-functional teams to deliver enterprise-grade AI solutions
- Mentor junior engineers and contribute to technical leadership, architecture discussions, and design reviews
Required Skills & Experience
- Strong hands-on experience building and deploying production-grade Generative AI and RAG systems
- Experience working on multi-agent or agentic AI architectures
- Strong proficiency in Python and backend/API development
- Hands-on experience with GCP AI/ML ecosystem including Vertex AI and BigQuery
- Solid understanding of LLM infrastructure, orchestration layers, and AI platform engineering
- Experience with CI/CD pipelines and Infrastructure as Code tools like Terraform
- Good understanding of GenAIOps/MLOps practices and model lifecycle management
- Strong system design and architecture experience for scalable AI platforms
- Exposure to enterprise application architecture and distributed systems
- Experience leading small engineering teams, mentoring developers, or owning technical delivery is preferred
- Understanding of AI safety, governance, and compliance best practices
Nice to Have
- Experience with LangChain, LlamaIndex, or similar frameworks
- Familiarity with RAG evaluation tools such as RAGAS or DeepEval
- Knowledge of Knowledge Graphs with RAG systems
- Experience working in multi-cloud environments (GCP + Azure)
- Exposure to BFSI or other regulated domains
What We’re Looking For
- Engineers who have built and deployed real-world GenAI systems at scale
- Strong backend engineering and systems-thinking mindset
- Ability to thrive in fast-paced enterprise environments
- Ownership mindset with strong communication and collaboration skills
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
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Bengaluru, Mumbai, and Trivandrum
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