AI Architect

Fa Etvl Saasfaprod1 Open · verified Nov 1, 2026

Pune Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at Fa Etvl Saasfaprod1. Pune.

Pay not stated AI Architect salary

RoleAI Engineering

SeniorityMid-level

LocationPune

PostedOct 27, 2026 · 5d ago

Role brief

aimlroles summary, based on the employer's posting.

What you'll do

Build multi-agent systems that coordinate autonomous negotiation, delegated tasks and shared state
Create MCP servers and clients that connect language models securely with data sources and enterprise tools
Set the internal AI platform’s architecture, then establish shared patterns and write architecture RFCs
Write production code and prototypes, tune service speed and scale, and test reliability
Guide junior engineers and align AI work with product, security and operations teams

What you bring

At least ten years in software architecture, including three or more years delivering production LLM applications
Deep knowledge of multi-agent frameworks such as LangGraph, AutoGen or CrewAI, plus MCP or comparable protocols
Strong skills in Python, TypeScript or Go, cloud-native tools, and hands-on RAG and vector database work
A bachelor’s degree or higher in computer science, engineering or a related discipline

Who this fits

This role suits a senior architect who can set technical direction while still producing code and prototypes. You’ll mentor junior engineers and explain complex AI work to technical and business audiences. The listed location is Pune, India.

From the employer

Zensar Technologies Limited seeks an experienced AI Architect to define and execute the architectural vision for its internal AI platform. You will create production‑grade multi‑agent frameworks, secure Model Context Protocol services, and robust RAG pipelines, while establishing engineering standards and mentoring teams to drive high‑throughput, low‑latency AI applications across the enterprise.

Design and implement multi‑agent orchestration frameworks for autonomous negotiation, task delegation, and state management.
Architect and develop scalable Model Context Protocol (MCP) servers and clients for secure LLM integration with data sources and enterprise tools.
Define the architectural vision for Zensar's internal AI platform, ensuring high throughput, low latency, and seamless developer workflows.
Write production‑ready code, build prototypes, and establish engineering best practices for AI application development.
Standardize architectural patterns across the organization and author comprehensive RFCs.
Mentor junior engineers and foster a culture of technical excellence.
Collaborate with product, security, and operations teams to align AI solutions with business goals.
Evaluate and integrate emerging AI SDKs, vector databases, and Retrieval‑Augmented Generation (RAG) pipelines.
Drive performance tuning, scalability testing, and reliability engineering for AI services.
Communicate complex technical concepts clearly to both technical and non‑technical stakeholders.

10+ years of software architecture experience, with at least 3 years building production‑grade LLM applications.
Deep expertise in multi‑agent frameworks such as LangGraph, AutoGen, or CrewAI.
Proven experience designing or implementing Model Context Protocol (MCP) or similar context‑sharing protocols.
Strong command of Python, TypeScript, or Go and cloud‑native technologies (AWS/GCP/Azure, Kubernetes, Docker).
Hands‑on experience with prompt engineering, Retrieval‑Augmented Generation (RAG) pipelines, and vector databases.
Demonstrated ability to produce high‑quality, production‑ready code and prototypes.
Outstanding verbal and written communication skills, with a track record of leading technical discussions.
Experience authoring architecture RFCs and establishing engineering standards.
Ability to translate complex AI concepts into actionable solutions for business stakeholders.
Bachelor’s or higher degree in Computer Science, Engineering, or a related field.

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