Technical Architect
Iris Software · Noida · onsite · Posted 56d ago
Undisclosed9–14 yrsfulltimeSourced from
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About this role
Job Summary
Technical Architect
We are looking for a GenAI Architect to design, build, and guide the implementation of Generative AI solutions across enterprise use cases.
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.
- 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
- Cloud Architecture & Deployments
- 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
- Cloud - GCP - Apigee API Management, API Gateway
Sourced from naukri
Skills
AutomationDevopsDockerKubernetesCustomer SupportTechnical Leadershipaws iamcloud servicesMLOpsworkflow automationgoogle cloud platformLarge Language Models (LLMs)API GatewaysArchitecturecomplianceMicrosoft AzureCloud ArchitectureData ScienceArtificial IntelligenceMachine Learning
About Iris Software
Iris Software
IT Services & Consulting
4.3k+
employees
1991
35 years old
Edison, New Jersey
United States (USA)
About
IT company for best tech-solutions to enhance business operations
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Culture
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