AI/ML Technical Lead – Generative AI, AI Agents & Intelligent Automation

Job Title: AI/ML Technical Lead – Generative AI, AI Agents & Intelligent Automation About the Role

We are seeking a highly skilled and hands-on AI/ML Technical Lead to drive our AI strategy, lead engineering teams, and build next-generation AI-powered products and intelligent automation solutions. This role requires deep expertise in Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, Voice AI, Multi-Agent Systems, and Intelligent Automation.

The ideal candidate will be responsible for architecting, developing, deploying, and scaling production-grade AI solutions while continuously evaluating and adopting emerging AI technologies that deliver measurable business value. This individual will serve as both a technical leader and innovation driver, helping shape the organization's AI vision and roadmap.

Key Responsibilities: AI Agent Development

Design, build, and deploy intelligent AI agents for enterprise and customer-facing applications.

Develop autonomous and multi-agent systems capable of reasoning, planning, decision-making, and task execution.

Build AI assistants capable of:

Natural human-like conversations

Context awareness

Persistent memory

Automated note-taking

Reminder management

Workflow execution

Meeting summarization

Personalized user interactions

Develop AI copilots, virtual employees, and domain-specific intelligent assistants.

Implement memory management, tool usage, task delegation, and autonomous workflow execution.

Generative AI & LLM Engineering

Develop advanced Generative AI applications using proprietary and open-source foundation models.

Design and implement:

Retrieval-Augmented Generation (RAG)

Prompt Engineering

Fine-Tuning

Function Calling

Context Management

Memory Systems

AI Knowledge Bases

AI Search Solutions

Evaluate, benchmark, and optimize AI models for accuracy, latency, scalability, and cost efficiency.

Integrate LLM-powered capabilities into enterprise platforms and business workflows.

Agent Orchestration & Intelligent Automation

Build and manage agent orchestration frameworks and agent communication architectures.

Develop multi-agent collaboration and workflow systems.

Integrate AI agents with APIs, databases, SaaS platforms, and enterprise applications.

Build intelligent automation solutions that streamline operations and reduce manual effort.

Design event-driven AI workflows and autonomous business process automation systems.

Conversational AI, Voice AI & Human Interaction

Design and develop conversational AI systems with natural and engaging interactions.

Build:

Voice Assistants

AI Receptionists

AI Customer Support Platforms

Real-Time Voice Agents

AI Meeting Assistants

Implement:

Speech-to-Text (STT)

Text-to-Speech (TTS)

Voice Cloning

Emotion-Aware Interactions

Human-Like Dialogue Systems

Develop AI-powered avatars and digital assistants for immersive user experiences.

AI Memory, Notes & Productivity Systems

Design persistent memory architectures for AI applications.

Develop systems capable of:

Remembering user preferences

Maintaining long-term context

Managing conversation history

Automatically generating notes and summaries

Scheduling reminders and follow-ups

Build intelligent productivity and knowledge management assistants.

Machine Learning & AI Engineering

Build, train, evaluate, and deploy machine learning models.

Develop AI solutions for:

Predictive Analytics

Recommendation Systems

Customer Intelligence

Personalization Engines

Classification Models

Natural Language Processing (NLP)

Computer Vision Applications

Continuously optimize model performance, accuracy, reliability, and scalability.

AI Product Development

Participate in end-to-end AI product architecture and development.

Translate business requirements into scalable AI-powered solutions.

Build reusable AI frameworks, accelerators, and internal platforms.

Develop AI-powered SaaS products and enterprise-grade applications.

AI Innovation & Emerging Technologies

Continuously research, evaluate, and adopt emerging AI technologies, frameworks, and platforms.

Stay current with advancements in:

Generative AI

Agentic AI

Multi-Agent Systems

Large Language Models (LLMs)

Small Language Models (SLMs)

Multimodal AI

Voice AI

Computer Vision

AI Avatars

AI Search

Intelligent Automation

Robotics & Autonomous Systems

AI Infrastructure & MLOps

Lead proof-of-concept initiatives and innovation programs.

Rapidly evaluate and implement newly released AI technologies and frameworks.

Recommend best-fit AI solutions aligned with business objectives and market opportunities.

Technical Leadership

Lead, mentor, and grow a high-performing AI/ML engineering team.

Establish AI architecture standards, development practices, and coding guidelines.

Conduct architecture reviews, design reviews, and technical planning sessions.

Collaborate closely with Product, Engineering, Operations, and Executive Leadership teams.

Drive an AI-first culture of innovation and experimentation.

Own technical delivery, solution quality, and AI project outcomes.

Required Technical Skills: Artificial Intelligence & Generative AI

Generative AI

Large Language Models (LLMs)

Small Language Models (SLMs)

Agentic AI

Multi-Agent Systems

Prompt Engineering

Fine-Tuning

Retrieval-Augmented Generation (RAG)

AI Search

AI Memory Systems

AI Copilots

Intelligent Automation

AI Frameworks & Platforms

Hands-on experience with one or more of:

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

OpenAI Agents SDK

LlamaIndex

Hugging Face

MCP (Model Context Protocol)

AI Workflow Platforms

Machine Learning & Data Science

Python

PyTorch

TensorFlow

Scikit-Learn

Deep Learning

NLP

Reinforcement Learning

Statistical Modeling

Voice AI & Multimodal AI

Speech-to-Text (STT)

Text-to-Speech (TTS)

Conversational AI

Voice AI

Audio Processing

Image Understanding

Video Understanding

Backend & Software Engineering

Python

FastAPI

REST APIs

GraphQL

Microservices Architecture

Event-Driven Systems

Vector Databases

Experience with one or more:

Pinecone

Weaviate

Qdrant

ChromaDB

Milvus

Cloud & Infrastructure

AWS

Microsoft Azure

Google Cloud Platform (GCP)

Docker

Kubernetes

CI/CD Pipelines

MLOps

Model Deployment & Monitoring

Experience RequiredMust Have

5+ years of experience in AI/ML Engineering.

2+ years of hands-on experience building Generative AI, LLM, or AI Agent solutions.

Proven experience leading engineering teams and AI initiatives.

Experience deploying AI solutions into production environments.

Strong system design, architecture, and problem-solving skills.

Ability to rapidly learn and adopt emerging AI technologies.

Preferred

Experience building enterprise AI copilots and intelligent assistants.

Experience taking AI products from concept to production.

Experience working with global clients and distributed teams.

Understanding of AI governance, security, compliance, and responsible AI practices.

Startup, SaaS, or product engineering experience is highly desirable.

Success Metrics (KPIs)

Successful deployment of AI products and solutions.

AI Agent task completion accuracy and effectiveness.

User adoption and satisfaction rates.

Reduction in manual effort through intelligent automation.

AI platform reliability, scalability, and performance.

Innovation initiatives delivered per quarter.

Time-to-market for AI products and features.

Revenue impact generated through AI-powered solutions.

Ideal Candidate

A highly proactive AI leader who can quickly research, learn, architect, build, deploy, optimize, and scale emerging AI technologies. The ideal candidate combines strong technical expertise with leadership capabilities and possesses the vision to transform cutting-edge AI advancements into practical, scalable, and commercially successful products. They thrive in fast-moving environments and are passionate about driving innovation through AI.