Technical Architect

Iris Software, Inc.; Dadri; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Iris Software is seeking a GenAI Architect to design, build, and guide GenAI solutions across enterprise use cases. You will work with LLMs, RAG, vector databases, and agentic AI frameworks, with a focus on cloud-native deployments and CI/CD automation.

You will collaborate with business stakeholders, data/ML teams, and engineering to deliver scalable, production-ready GenAI platforms and applications. The role demands hands-on expertise and architectural leadership in GenAI.

Qualifications

• GenAI algorithms and LLM concepts, prompting, RAG and embeddings.
• Enterprise GenAI use case design (docs, copilots, summaries, search).
• Evaluation techniques for groundedness, relevance and latency/cost trade-offs.
• Hands-on with vector DBs and retrieval concepts (indexing, ANN, hybrid search).

Responsibilities

• Architect end-to-end GenAI solutions with RAG pipelines and multi-agent workflows.
• Translate business problems into GenAI use cases and roadmaps.
• Design retrieval systems with embeddings, chunking, metadata filters and reranking.
• Select and integrate vector databases; optimize indexing and relevance.
• Build agentic systems using LangChain, LangGraph and related tools.
• Define cloud patterns for scalable GenAI deployments and CI/CD integration.

Skills

GenAI Architecture

Vector Databases

Agentic AI Frameworks

Cloud GenAI Workloads

CI/CD & Productionization

GenAI Use Cases

Tools

LangChain

LangGraph

MCP

Pinecone

FAISS

Weaviate

Chroma

Milvus

Azure AI Search

Elastic Vector

Job description

Why Join Iris?

Are you ready to do the best work of your career at one of India’s Top 25 Best Workplaces in IT industry? Do you want to grow in an award-winning culture that truly values your talent and ambitions? Join Iris Software — one of the fastest-growing IT services companies— where you own and shape your success story.

About Us

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.

Working with Us

At Iris, every role is more than a job — it’s a launchpad for growth.

Our Employee Value Proposition, “Build Your Future. Own Your Journey.” reflects our belief that people thrive when they have ownership of their career and the right opportunities to shape it.

We foster a culture where your potential is valued, your voice matters, and your work creates real impact. With cutting-edge projects, personalized career development, continuous learning and mentorship, we support you to grow and become your best — both personally and professionally.

Curious what it’s like to work at Iris? Head to this video for an inside look at the people, the passion, and the possibilities. Watch it here.

Job Description

We are looking for a GenAI Architect to design, build, and guide the implementation of Generative AI solutions across enterprise use cases. The role requires strong hands‑on and architectural expertise in LLMs, RAG, vector databases, and agentic AI frameworks, along with experience in cloud-native deployments and CI/CD automation. You will collaborate with business stakeholders, data/ML teams, and engineering teams to deliver scalable, secure, and production‑ready GenAI platforms and applications.

Key Responsibilities

• Architect and design end-to-end GenAI solutions including RAG pipelines, agentic workflows, and multimodal use cases.
• Translate business problems into GenAI-driven use cases, solution blueprints, and implementation roadmaps.
• Design and implement retrieval systems using embeddings, chunking strategies, metadata filters, reranking, and evaluation metrics.
• Select and integrate vector databases and optimize indexing, retrieval performance, and relevance tuning.
• Build agentic systems using frameworks such as LangChain, LangGraph, and related orchestration tools.
• Define cloud architecture patterns for scalable, secure, and reliable GenAI deployments.
• Drive productionization using CI/CD pipelines, containerization using best practices.
• Ensure responsible AI practices including security, governance, privacy, compliance, and monitoring.
• Provide technical leadership, reviews, mentoring, and best‑practice guidance to engineering teams.
• Collaborate with product and delivery teams to ensure solution alignment with timelines and business outcomes.

Primary Skills (Must Have)

GenAI / LLM Architecture & Algorithms

• Strong knowledge of GenAI algorithms and LLM concepts: prompting, fine‑tuning vs RAG, embeddings, context windows, token limits, hallucination control.
• Experience designing enterprise GenAI use cases (document Q&A, copilots, summarization, search, workflow automation, customer support, knowledge assistants).
• Understanding of evaluation techniques: groundedness, relevance, faithfulness, latency/cost trade‑offs.

Vector Databases & Retrieval Systems

• Hands‑on understanding of vector databases and similarity search concepts: embeddings, indexing, ANN search, hybrid search, metadata filtering.
• Experience with tools like Pinecone, FAISS, Weaviate, Chroma, Milvus, Azure AI Search / Elastic (vector) (any relevant combination).

Agentic AI Frameworks

• Strong working knowledge of agentic frameworks such as: LangChain
• LangGraph
• MCP
• Tool calling / function calling, memory, planning, multi‑agent workflows, guardrails

Experience with cloud services and architecture for GenAI workloads:

• compute, networking, storage, IAM/security, logging/monitoring
• Knowledge of cloud components supporting AI/ML solutions (managed services preferred).

CI/CD and Productionization

• Experience implementing CI/CD pipelines for GenAI apps and services.
• Strong understanding of deployment patterns: containers (Docker), orchestration (Kubernetes), API deployment, model endpoint integration
• Familiarity with DevOps/MLOps practices: testing, observability, rollback, scaling, cost controls.

Data Science and Machine Learning - Data Science and Machine Learning - Gen AI

Beh - Communication

Development Tools and Management - Development Tools and Management - CI/CD

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 here to view the benefits.