AI Solution Architect

Nexcen It Services; Dadri, Gurugram District, Delhi; On-site; INR 4,500,000 - 7,500,000; Full time

Benefits offered by this job

Health insurance

Job summary

Nexcen It Services is seeking an AI Architect to define end-to-end agent frameworks, align with enterprise environments, and drive guardrails with cross-functional teams. You will shape reference architectures for single and multi-agent systems, design LLM-driven workflows, and ensure scalable, secure deployments across cloud platforms.

The role demands deep expertise in LLMs, prompt engineering, and agent orchestration tools, with hands-on experience in LangGraph, AutoGen, CrewAI, Semantic

Qualifications

• Deep expertise in large language models and reasoning frameworks.
• Hands-on with agent frameworks and orchestration tools.
• Strong grounding in RAG, embeddings, and vector databases.

Responsibilities

• Translate business problems into agent-driven solution blueprints.
• Partner with senior stakeholders to identify high-impact use cases.
• Define reference architectures for agentic AI systems.
• Establish AI guardrails covering safety, bias, and compliance.
• Drive standards for agent testing, evaluation, and certification.
• Oversee architecture, scalability, and cost optimization of AI platforms.

Skills

LLM expertise

Agent frameworks

LangGraph

AutoGen

CrewAI

Semantic Kernel

RAG & embeddings

LoRA/QLoRA

Python

Azure

AWS

GCP

Observability

Cost management

Enterprise data integration

Tools

Azure

AWS

GCP

Job description

Role Summary

The architect will define endtoend agent frameworks, ensure alignment with available enterprise environment, guardrails, and partner closely with engineering, QE, security, and compliance teams.

Job Description

Business & Stakeholder Leadership

• Translate business problems into agentdriven solution blueprints.
• Partner with senior stakeholders to identify highimpact use cases (automation, decision support, quality, operations).
• Provide executivelevel guidance on agentic AI adoption, maturity models, and roadmaps.
• Support client conversations, RFPs, solution pitches, and thought leadership.

Architecture & Design

• Define reference architectures for agentic AI systems (singleagent, multiagent, hierarchical, toolusing agents).
• Design LLMdriven workflows integrating reasoning, planning, memory, tools, and humanintheloop controls.
• Architect RAGbased and toolaugmented agents using enterprise data sources, APIs, and workflows.
• Ensure scalability, resilience, observability, and cost optimization of agent platforms.

Governance, Risk & Guardrails

• Establish AI guardrails covering safety, bias, explainability, auditability, and regulatory compliance.
• Define agent lifecycle management (design, testing, deployment, monitoring, retirement).
• Partner with Risk, Legal, Security, and QE teams to ensure model risk management (MRM) and enterprise readiness.
• Drive standards for agent testing, validation, and certification (functional, nonfunctional, and ethical).

Core AI & GenAI

• Deep expertise in LLMs, prompt engineering, and reasoning frameworks.
• Handson experience with agentic frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, custom agent orchestration).
• Strong understanding of RAG, embeddings, vector databases, and knowledge grounding.
• Experience with finetuning techniques (LoRA / QLoRA) and evaluation strategies.

Architecture & Engineering

• Strong background in distributed systems, APIs, microservices, and cloudnative architectures.
• Proficiency in Python and familiarity with enterprise integration patterns.
• Experience with cloud platforms (Azure, AWS, GCP) and secure enterprise deployments.
• Knowledge of observability, monitoring, and cost management for AI systems.