Role Overview

We are looking for a Lead AI Engineer / AI Architect to design, build, and scale production-grade AI systems.

This role combines hands-on AI engineering with system architecture leadership. The candidate will be responsible for designing scalable AI platforms, mentoring engineers, and ensuring that machine learning models are successfully deployed into real-world applications.

The ideal candidate has strong expertise in machine learning, backend engineering, distributed systems, and modern LLM ecosystems, along with experience designing scalable AI architectures.

Key Responsibilities

AI System Architecture

- Design scalable architectures for AI-powered products and services
- Architect end-to-end ML systems including training, deployment, and monitoring
- Define architectural standards for AI services, APIs, and data pipelines
- Design distributed AI systems that support large-scale inference and data processing

AI Engineering & Development

- Build and deploy production AI/ML systems
- Develop APIs and services exposing AI capabilities
- Implement LLM-powered systems including:
- RAG pipelines
- Semantic search
- Conversational AI systems
- Optimize model performance, latency, and scalability

AI Platform & Infrastructure

- Design and maintain ML infrastructure for training and deployment
- Build scalable inference systems for ML and LLM models
- Implement CI/CD pipelines for ML systems
- Deploy services using containerized infrastructure

Technical Leadership

- Lead AI engineering teams and mentor junior engineers
- Conduct architecture and code reviews
- Define engineering standards for AI development
- Guide teams in implementing scalable AI solutions

Cross-Team Collaboration





- Work closely with product and engineering leadership
- Translate business problems into scalable AI solutions
- Coordinate with data engineering, backend, and platform teams

Required Skills

Programming & Software Engineering

- Expert-level Python
- Solid experience writing production-grade systems
- Experience designing scalable backend services

Machine Learning & AI

Strong experience with:

- Supervised and unsupervised learning
- Model evaluation and optimization
- Feature engineering
- Model deployment pipelines

Experience with:

- PyTorch / TensorFlow
- Scikit-learn

LLM & Modern AI Stack

Experience with:

- LLM APIs (OpenAI, Claude, etc.)
- RAG architectures
- LangChain / LlamaIndex
- Embedding models and semantic search
- Prompt engineering and LLM orchestration

Databases

Experience working with:

- PostgreSQL
- MongoDB
- Vector databases (Pinecone, Weaviate, FAISS, Chroma)

Infrastructure & Deployment

- Docker
- Kubernetes (preferred)
- Cloud platforms (AWS / GCP / Azure)
- CI/CD pipelines

System Architecture

Experience designing:

- Distributed AI systems
- Microservices architectures
- Data pipelines and ML workflows
- High-performance inference systems

Ideal Candidate Profile

- 8–15 years experience in AI / ML / Backend engineering
- Experience designing AI system architectures
- Experience leading AI engineering teams
- Strong problem-solving and system design skills
- Experience building production AI products at scale

What We Are NOT Looking For

- Profiles focused only on research or academic ML
- Candidates who primarily worked in notebooks without production deployment experience
- Engineers without strong software engineering fundamentals

📌 Lead AI Engineer / AI Architect (Nashik)
🏢 GrowthArc
📍 Nashik