Agentic/AI lead/architect with Claude/code/LLM skills1

Mployee.me; India; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Mployee.me is seeking a senior GenAI Architect to define enterprise reference architectures for Agentic AI and LLM-powered platforms. You will own tool-calling, memory, planning, and execution layers, while guiding cloud deployment patterns and cost-latency trade-offs.

You will mentor senior engineers, collaborate with clients and product owners to shape AI roadmaps, and ensure secure, governance-driven GenAI systems across regulated environments.

Qualifications

• 12+ years of total experience with Generative AI / LLM-based systems.
• Strong background in Data Engineering or Data Science (mandatory).
• Experience designing agentic AI systems (ReAct, Plan-and-Execute, multi-agent setups).
• Hands-on experience with Claude/Anthropic ecosystem and other enterprise LLMs.
• Proficiency in prompt engineering, orchestration, and tool/calling patterns.

Responsibilities

• Define enterprise reference architectures for Agentic AI and LLM-powered platforms.
• Oversee tool-calling, function orchestration, and memory/planning/execution layers.
• Own architectural decisions for Claude and other enterprise-grade LLMs.
• Design secure GenAI systems with guardrails, privacy, and safety.
• Lead RAG architecture and data pipelines; partner with Data Engineering teams.
• Drive production readiness with API-first design, CI/CD, monitoring, and cost tracking.
• Establish engineering standards and reusable accelerators across accounts.
• Review cloud architecture for scalable, compliant AI deployments.
• Mentor engineers and architects on agentic patterns and LLMin engineering.
• Engage with clients to shape AI roadmaps and solution designs.

Skills

Generative AI

LLM architectures

Prompt engineering

Agentic AI workflows

Data engineering

Data science

Leadership

Mentoring engineers

Tools

Claude / Anthropic

OpenAI models

Mistral

LLaMA

FAISS

Pinecone

Chroma

FastAPI

Azure

AWS

GCP

Job description

Key Responsibilities

GenAI & Agentic AI Architecture

• Define enterprise reference architectures for Agentic AI and LLM-powered platforms, including: - Single-agent and multi-agent systems
• Tool-calling and function orchestration
• Memory, planning, and execution layers
• Own architectural decisions for Claude / Claude Code and other enterprise-grade LLMs, including model selection, deployment patterns, and cost-latency trade-offs.
• Design secure-by-default GenAI systems incorporating: - Guardrails and policy enforcement
• Data privacy, PII handling, and prompt safety
• Controlled tool execution in regulated environments

RAG, Knowledge & Data Systems

• Architect large-scale RAG solutions, covering: - Data ingestion and curation pipelines
• Chunking and embedding strategies
• Vector databases and hybrid search
• Evaluation and feedback loops
• Partner with Data Engineering teams to ensure data quality, lineage, observability, and governance for AI-driven systems.

Platform & Engineering Excellence

• Drive production readiness of GenAI systems: - API-first design (FastAPI / REST / event-driven)
• CI/CD for LLM workflows
• Monitoring, evaluation, and cost tracking
• Establish engineering standards, reusable frameworks, and accelerators for faster adoption across EXL accounts.
• Review and influence cloud architecture (Azure / AWS / GCP) for scalable and compliant AI deployments.

Leadership & Stakeholder Engagement

• Act as a technical authority for GenAI across delivery teams and client engagements.
• Mentor senior engineers, tech leads, and architects on agentic patterns and advanced LLM engineering.
• Partner with clients, product owners, and domain SMEs to shape AI roadmaps, solution designs, and value articulation.

Mandatory Skills & Experience

12+ years of total experience with deep hands-on expertise in Generative AI / LLM-based systems, and strong prior background in Data Engineering or Data Science (mandatory).

Generative AI / LLM Expertise

• Deep hands-on experience with: - Claude / Anthropic ecosystem (including Claude Code exposure is a strong plus)
• Other enterprise LLMs (OpenAI, Mistral, LLaMA, etc.)
• Strong command over: - Prompt engineering, prompt orchestration, and agent workflows
• Tool/function calling, planning-execution loops
• LLM and RAG evaluation techniques (precision, grounding, faithfulness)

Agentic & RAG Architecture

• Proven experience designing: - Agentic AI systems (ReAct, Plan-and-Execute, multi-agent setups)
• RAG architectures using vector databases (FAISS, Pinecone, Chroma, etc.)
• Strong understanding of hallucination mitigation, guardrails, and safety frameworks.

Core Engineering & Platform Skills

• Expert-level Python engineering (production-grade systems).
• Strong experience with cloud-native AI solutions on Azure, AWS, or GCP.
• API design, microservices, and event-driven architectures.

Mandatory Prior Background

• Data Engineering or Data Science experience is non-negotiable, including: - Data pipelines / ETL / ELT / orchestration
• ML or NLP model lifecycle
• Analytics platforms or data product engineering

Good-to-Have / Preferred

• Fine-tuning and adaptation strategies (LoRA / PEFT / prompt tuning).
• Experience with MLOps / LLMOps platforms and observability stacks.
• Experience delivering GenAI solutions in regulated industries (Insurance, Healthcare, BFS).
• Exposure to enterprise AI governance frameworks.