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 contemporary 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 Strong 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 (India)
🏢 GrowthArc
📍 India