Senior Technical Architect

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At Iris Software, our vision is to be our client's most trusted technology partner, and the first choice for the industry's top professionals to realize their full potential.With over 4,300 associates across India, U.S.A, and Canada, we help our enterprise clients thrive with technology-enabled transformation across financial services, healthcare, transportation & logistics, and professional services.Our work covers complex, mission-critical applications with the latest technologies, such as high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation.

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Job Description

We are looking for a GenAI Architect to design and scale enterprise Generative AI solutions. This role requires strong hands-on and architectural expertise in LLMs, RAG systems, vector databases, and agentic AI frameworks, along with experience deploying production-grade GenAI platforms on the cloud.

Key Responsibilities

• Design end-to-end GenAI architectures including RAG pipelines, agent workflows, and multimodal use cases.
• Translate business needs into GenAI use cases, architecture designs, and implementation roadmaps.
• Architect and optimize retrieval systems (embeddings, chunking, metadata filtering, reranking, evaluations).
• Select and integrate vector databases, tuning for performance, relevance, and scalability.
• Build agentic AI solutions using LangChain, LangGraph, MCP, and tool-calling frameworks.
• Define cloud-native architectures for secure, scalable GenAI deployments.
• Drive productionization using CI/CD pipelines, containers, observability, and cost controls.
• Ensure Responsible AI practices covering security, privacy, compliance, and monitoring.
• Provide technical leadership and mentoring across engineering teams.

Required Skills

GenAI & LLM Architecture

• Strong understanding of LLMs: prompting, RAG vs fine-tuning, embeddings, context limits, hallucination control.
• Experience delivering enterprise GenAI solutions (copilots, document Q&A, summarization, assistants).
• Knowledge of evaluation metrics: relevance, groundedness, latency, and cost.

Retrieval & Vector Databases

• Experience with embeddings, ANN search, hybrid retrieval, and metadata filtering.
• Hands-on exposure to vector stores such as Pinecone, FAISS, Weaviate, Chroma, Milvus, Azure AI Search, Elastic.

Agentic AI

• Working knowledge of LangChain, LangGraph, MCP, multi-agent workflows, memory, and guardrails.

Cloud & DevOps

• Experience designing GenAI workloads on AWS / Azure / GCP.
• Strong understanding of Docker, Kubernetes, API deployments, CI/CD, and MLOps practices.

Good to Have

• RAG optimization (advanced chunking, reranking, feedback loops).
• LLM integrations (OpenAI, Azure OpenAI, Anthropic, Gemini, open-source models).
• GenAI observability, prompt/version management, and Responsible AI controls.

Perks and Benefits for Irisians
Iris provides world-class benefits for a personalized employee experience. These benefits are designed to support financial, health and well-being needs of Irisians for a holistic professional and personal growth. Click to view the benefits.