AI Architect

Genzeon Global; Hyderabad; Hybrid; INR 3.800.000 - 5.500.000; Vollzeit

Benefits dieser Stelle

Hybrid work model

Zusammenfassung

Genzeon Global is seeking an experienced AI Architect in India (Hybrid) to lead the design and delivery of AI-native systems. The role focuses on integrating GenAI, LLMs, and agentic AI across client engagements, ensuring scalable, secure architectures built from the ground up around AI capabilities.

You will guide architecture standards, drive technical delivery, and mentor engineers and data scientists while collaborating with stakeholders to translate business problems into robust AI

Qualifikationen

• 8-12 years of tech experience with 4-5 years in AI/ML architecture.
• Proven track record delivering production AI systems, not just POCs.
• Hands-on GenAI and LLMs with RAG, embeddings, fine-tuning.
• Experience designing agentic AI systems with multi-agent orchestration.
• Strong ML/AI foundation plus GenAI and toolchains.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, HuggingFace).

Aufgaben

• Architect end-to-end AI-native systems built around AI capabilities.
• Define reference architectures, patterns, standards for AI/ML.
• Lead model selection, data architecture, and scalable AI delivery.
• Oversee MLOps/LLMOps, CI/CD, monitoring and observability.
• Collaborate with data engineers to ensure high-quality data pipelines.
• Mentor engineers and data scientists in AI-native design.

Kenntnisse

AI architecture

GenAI & LLMs

Agentic AI

Python

MLOps/LLMOps

Cloud-native architecture

Security & compliance

Communication

Ausbildung

Bachelor's or Master's in CS/Engineering/Data Science

Tools

Pinecone

Weaviate

FAISS

Milvus

LangChain

LangGraph

Semantic Kernel

AutoGen

CrewAI

Jobbeschreibung

GenAI, Agentic AI & AI-Native Engineering

EXPERIENCE

8 - 12 years

LEVEL

Senior Architect

LOCATION

India (Hybrid) - Genzeon offices

EMPLOYMENT TYPE

Full-Time

FUNCTION

Technology / AI & Engineering

REPORTS TO

Head of AI / Engineering Leadership

Genzeon Services is atechnology and business process solutions company that helps healthcare payers,providers, and life sciences organizations modernize their operations throughdigital transformation, automation, and applied AI. We combine deep domainexpertise with modern engineering practices to build intelligent, scalablesystems that solve real business problems.

RoleSummary

We are looking for anexperienced AI Architect who has worked extensively on AI-led projects andAI-Native Engineering to design, build, and scale intelligent systems acrossour client engagements. This role goes beyond bolting AI onto existingapplications - the ideal candidate has architected solutions where AI(including LLMs and agentic systems) is a first-class, foundational componentof the system design. You will define architecture standards, lead technicaldelivery, and act as the primary AI technology advisor across multipleengagements and teams.

KeyResponsibilities

• Architect end-to-end AI-native systems - applicationsdesigned from the ground up around AI capabilities rather than retrofitted withAI features.
• Define reference architectures, design patterns, andtechnical standards for AI/ML and GenAI solutions across the organization.
• Evaluate and select the right architecture (RAG,fine-tuning, agentic workflows, hybrid retrieval, multi-model orchestration)based on business requirements, cost, latency, and accuracy trade-offs.
• Own technical decision-making on model selection, dataarchitecture, integration patterns, and scalability for AI systems.
• Ensure AI solution designs address security, dataprivacy, compliance (including healthcare/HIPAA where applicable), andresponsible AI principles.

GenAI,LLMs & Agentic AI

• Design and oversee implementation of LLM-poweredapplications, including RAG pipelines, prompt engineering frameworks, andfine-tuning/adaptation strategies.
• Architect multi-agent and agentic AI systems (planning,tool use, memory, orchestration) for complex, multi-step business workflows.
• Drive adoption of frameworks such as LangChain,LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent for buildingproduction-grade agentic solutions.
• Stay current with the rapidly evolving GenAI ecosystem(foundation models, vector databases, evaluation frameworks) and translateemerging capabilities into practical solution designs.
• Define and guide implementation of MLOps/LLMOpspractices - CI/CD for models and prompts, automated evaluation, monitoring, andobservability for AI systems in production.
• Architect scalable AI infrastructure across cloudplatforms (Azure, AWS, or GCP), including vector stores, model-serving layers,and orchestration pipelines.
• Establish practices for model/prompt versioning, costmonitoring, performance benchmarking, and continuous improvement of deployed AIsystems.
• Partner with data engineering to ensure high-quality,well-governed data pipelines feeding AI systems.

Leadership& Stakeholder Collaboration

• Act as the primary technical advisor on AI architecturefor client engagements, presales, and internal capability building.
• Collaborate with product owners, business stakeholders,and delivery teams to translate business problems into feasible,well-architected AI solutions.
• Mentor engineers and data scientists on AI-nativedesign principles, MLOps practices, and responsible AI development.
• Contribute to proposals, solution estimations, andtechnical due diligence for new AI opportunities.

RequiredQualifications

• 8-12 years of overall technology experience, with atleast 4-5 years focused substantially on AI/ML architecture and delivery.
• Demonstrated track record architecting and deliveringproduction AI systems - not just prototypes or POCs.
• Hands-on depth in Generative AI and LLMs: RAGarchitectures, prompt engineering, embeddings, vector databases (e.g.,Pinecone, Weaviate, FAISS, Milvus), and fine-tuning approaches.
• Practical experience designing or implementing agenticAI systems (multi-agent orchestration, tool-calling, autonomous workflows).
• Strong foundation in traditional ML/AI(supervised/unsupervised learning, model evaluation) in addition to GenAI.
• Proficiency in Python and familiarity with ML/AIframeworks (PyTorch, TensorFlow, Hugging Face, scikit-learn).
• Solid understanding of cloud-native architecture and AIservices on Azure, AWS, or GCP (e.g., Azure OpenAI, AWS Bedrock, Vertex AI).
• Experience with MLOps/LLMOps tooling and practices -containerization (Docker/Kubernetes), CI/CD, model monitoring, andobservability.
• Strong software architecture fundamentals - APIs,microservices, event-driven design, and system integration patterns.
• Excellent communication skills with the ability toexplain complex AI concepts to both technical and non-technical stakeholders.

Preferred/ Good to Have

• Experience in healthcare, payer/provider, or lifesciences domains.
• Familiarity with agentic frameworks such as LangGraph,AutoGen, CrewAI, or Semantic Kernel.
• Exposure to responsible AI practices - modelgovernance, bias evaluation, and explainability.
• Prior experience in a client-facing architect ortechnical lead role within a consulting or IT services environment.
• Relevant certifications (e.g., Azure AI Engineer, AWSMachine Learning Specialty, Google Cloud ML Engineer).

Education

• Bachelor's or Master's degree in Computer Science,Engineering, Data Science, or a related field (or equivalent practicalexperience).

WhatWe Offer

The opportunity to architectcutting-edge AI-native systems at enterprise scale, work alongside acollaborative engineering culture, and shape Genzeon's AI capability anddelivery standards across high-impact client engagements.