Ai Engineering Manager

Boots2suits Consultancy; India; Hybrid; INR 6,300,000 - 7,700,000; Full time

Job summary

EMB Global is seeking an Engineering Manager AI in Gurugram. This player-coach role requires leading a team to build production-grade AI solutions.

Ideal candidates have 10+ years of software engineering experience with strong leadership skills and hands-on expertise in Multi-Agentic AI, GenAI, and RAG systems. The role involves managing technical delivery while driving hiring and team development.

Qualifications

• 10+ years of hands‑on software engineering experience.
• Strong development/production engineering background.
• Demonstrated experience managing and leading engineering teams.
• Strong hands‑on experience with Agentic AI, GenAI/LLM and RAG systems.
• Experience building and deploying production-grade AI solutions.
• Strong technical leadership and delivery ownership.
• Ability to remain technically involved while managing the engineering team.

Responsibilities

• Lead and develop a team of AI/ML and software engineers.
• Drive the development of Multi-Agentic AI systems and production-grade AI solutions.
• Provide technical direction around architecture, design and engineering practices.
• Ensure engineering quality, testing, CI/CD and production reliability.
• Communicate technical progress, risks and delivery status to senior leadership and clients.

Skills

Multi-Agentic AI

AI Orchestration

RAG (Retrieval-Augmented Generation)

GenAI / Generative AI

LLMs

Python

AWS

Azure

API development

CI/CD

Tools

Cloud

Vector databases

Agent frameworks

Prompt engineering

Job description

Engineering Manager AI
Location: Gurugram
Experience: 10+ Years
Employment Type: Full-time
Work Model: Hybrid
Working Days: 5 Days
CTC: Up to 70 LPA (All Fixed)
Notice Period: Preferably 45 Days | Maximum 60 Days

About the Role

EMB Global is looking for an Engineering Manager AI to lead an engineering team building production-grade Agentic AI and GenAI solutions for enterprise clients.

This is a player-coach role, requiring a strong software/development background along with engineering leadership. The candidate will be responsible for technical direction, team development, delivery and engineering quality while remaining hands‑on with technical discussions, architecture and critical engineering problems.

Key Responsibilities

• Lead and develop a team of AI/ML and software engineers.
• Drive the development of Multi-Agentic AI systems and production-grade AI solutions.
• Own AI orchestration, agent workflows and RAG pipelines.
• Provide technical direction around architecture, design and engineering practices.
• Review technical designs and code and help resolve complex engineering challenges.
• Plan and manage engineering delivery, timelines and sprints.
• Drive hiring, onboarding, performance management and career development.
• Ensure engineering quality, testing, CI/CD and production reliability.
• Work with architects, product managers and delivery teams to translate requirements into engineering solutions.
• Drive adoption of AI evaluation, guardrails and observability practices.
• Communicate technical progress, risks and delivery status to senior leadership and clients.

Mandatory Skills

Multi-Agentic AI
AI Orchestration
RAG (Retrieval-Augmented Generation)
Strong production/development-side engineering experience

Other Relevant Skills

• GenAI / Generative AI
• LLMs
• Python
• AWS / Azure / Cloud
• Agent frameworks such as LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands or Semantic Kernel
• API development
• CI/CD
• Vector databases
• Prompt engineering
• AI evaluation, guardrails and observability

Candidate Profile

• 10+ years of hands‑on software engineering experience.
• Strong development/production engineering background.
• Demonstrated experience managing and leading engineering teams.
• Strong hands‑on experience with Agentic AI, GenAI/LLM and RAG systems.
• Experience building and deploying production-grade AI solutions.
• Strong technical leadership and delivery ownership.
• Ability to remain technically involved while managing the engineering team.

Preferred: Experience with distributed/hybrid teams, enterprise integrations, fine‑tuning/open‑weight models, Middle East stakeholders and relevant AWS/Azure certifications.