AI Architect

Location: Pune  •  Level: Mid Level  •  Openings: 1  •  Type: Full-time
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Job description

1. Job Details
Job Title: AI Architect
Job Location: Pune
2. Candidate Expectations
Total Experience and Relevant Experience – 6+ Years
Candidate Location : Pune
Skills –  LLMs, RAG, AI Agents, Vector Databases, LangGraph, LangChain, LlamaIndex, Semantic Kernel, MCP, A2A, Multi-Agent Architectures, Prompt Engineering, AI Observability, AI Evaluation Frameworks (Evals), FastAPI, REST APIs, Python, Azure OpenAI, AWS Bedrock, Google Vertex AI, Docker, Kubernetes, CI/CD, Enterprise GenAI Solutions.
Candidate Industry (BPO / KPO / GBS / GCC / GSS / Captive Shared Services)
Diversity – N/A
3. Education and Certification
Qualification: Mandatory: BE/B.Tech/MBA/BCA/MCA
Specific Remarks: Distance education not accepted, 15 years regular stream mandatory, etc.
4. Detailed Job Description
Key Responsibilities:
Define and own end-to-end AI solution architecture for enterprise-scale Generative AI applications.
Design and implement AI Agents, RAG applications, and multi-agent ecosystems for complex business workflows.
Architect scalable AI platforms leveraging LLMs, Vector Databases, autonomous agents, and orchestration frameworks.
Build advanced GenAI solutions using LangGraph, LangChain, LlamaIndex, Semantic Kernel, and related frameworks.
Design robust RAG pipelines involving document ingestion, chunking, embedding generation, vector indexing, retrieval, and response generation.
Define MCP (Model Context Protocol), A2A (Agent-to-Agent) communication patterns, and multi-agent collaboration architectures.
Establish AI evaluation frameworks to measure model accuracy, relevance, hallucination rates, latency, cost, and business impact.
Develop prompt engineering strategies, context management techniques, AI guardrails, and responsible AI controls.
Integrate AI applications with enterprise systems, APIs, databases, and external tools.
Architect cloud-native AI solutions on Azure, AWS, and GCP platforms.
 Lead PoC development, technical discovery workshops, and client-facing solution discussions.
Collaborate with engineering, security, infrastructure, and business teams to ensure production-grade AI deployments.
Drive observability, monitoring, governance, performance optimization, and continuous improvement initiatives.
Mentor development teams and establish AI architecture best practices across projects.
 
5. Key Skills : Mandatory Key Skills:
Strong expertise in Python, AI/ML, and Generative AI solution architecture.
Hands-on experience with LLMs, RAG, AI Agents, and Vector Databases.
Expertise in LangGraph, LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
Strong understanding of Prompt Engineering, AI Observability, and LLM Evaluation Frameworks (Evals).
Experience designing MCP, A2A, and Multi-Agent Architectures.
Proficiency with REST APIs, FastAPI, Git, and Microservices-based integrations.
Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar AI platforms.
Strong knowledge of Docker, Kubernetes, CI/CD, and cloud-native deployments.
Experience implementing enterprise-scale GenAI solutions in production environments.
Strong architecture, stakeholder management, and client-facing communication skills.
Ability to work in ambiguous environments and rapidly transform business requirements into scalable AI solutions.
Experience with AI governance, security, compliance, and responsible AI practices.
Exposure to regulated industries such as Healthcare, Life Sciences, Banking, or Manufacturing is preferred.
 
6.Good to Have Skills: N/A

Job ID: 2085