Lead AI/ML Engineer

Armakuni; Ahmedabad District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Armakuni seeks a lead AI/ML Engineer with 6+ years of hands-on experience to design, deploy, and scale AI/ML and Generative AI solutions. Lead a team across LLMs, CV, ML, and data science, mentoring engineers and defining architecture for cloud deployments.

The role covers prototyping through production, with emphasis on Retrieval-Augmented Generation, prompt engineering, and enterprise-grade pipelines using AWS SageMaker and modern GenAI frameworks.

Qualifications

• 6+ years in AI/ML with 3+ years in Generative AI and LLMs.
• Strong Python proficiency and ML library exposure (Scikit-learn, XGBoost, LightGBM, CatBoost).
• Deep familiarity with OpenAI (GPT-4/4o), Claude, Gemini, LLaMa, DeepSeek, etc.
• Experience with GenAI tooling: Langchain, Langfuse, Crew AI, LLAMA Index, Langgraph.
• Experience with vector stores: Pinecone, FAISS, OpenSearch, Chroma.
• Hands-on with PyTorch and TensorFlow; AWS SageMaker/BEDROCK usage.
• REST APIs (FastAPI, Uvicorn, Flask), Docker; SQL & NoSQL databases; Redis/Memcached.

Responsibilities

• Drive AI/ML and Generative AI vision and roadmap.
• Mentor engineers and data scientists; lead architecture decisions.
• Translate business problems into scalable AI/ML solutions.
• Own end-to-end AI lifecycle from prototyping to production.

Skills

Python

LLMs

Generative AI

Langchain

Vector Databases

PyTorch

TensorFlow

AWS SageMaker

Model Deployment

Prompt Engineering

Team Leadership

Tools

Langchain

Langgraph

Langfuse

Crew AI

LLAMA Index

Job description

Job Summary: We are looking for a highly skilled Lead AI/ML Engineer with 6+ years of hands-on experience in designing, deploying, and scaling AI/ML and Generative AI solutions. The ideal candidate will lead technical efforts across a wide spectrum of AI technologiesincluding large language models (LLMs), computer vision, machine learning, and data science—to solve high-impact business problems. This is a technical leadership role that involves mentoring team members, shaping architecture decisions, and driving end-to-end AI solution delivery across cloud-based environments.

Key Responsibilities:

Leadership & Strategy

• Drive the technical vision and roadmap for AI/ML and Generative AI initiatives.
• Lead and mentor a team of AI/ML engineers and data scientists, conducting regular code reviews and guiding solution architecture.
• Collaborate with cross-functional stakeholders to translate business problems into scalable AI/ML solutions.
• Own the AI/ML lifecycle-from prototyping and experimentation to production deployment and monitoring.

Generative AI & LLMs

• Architect and lead the development of scalable Generative AI solutions using AWS Cloud and modern frameworks.
• Deep experience in working with large language models (LLMs) including fine-tuning, evaluation, and deployment.
• Expertise in prompt engineering, agentic workflows, and custom LLM development.
• Proficient with Langchain, Langgraph, Langfuse, Crew AI, and other GenAI frameworks.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise applications.

Machine Learning & Data Science

• Solve complex machine learning problems using supervised, unsupervised, and deep learning methods.
• Lead the implementation of ML pipelines including automated data preprocessing, training, validation, and monitoring.
• Manage ML lifecycle using AWS SageMaker, including model versioning, drift detection, and retraining strategies.
• Apply advanced analytics, time series forecasting, and predictive modeling techniques.

Skills & Qualifications:

• 6+ years of experience in AI/ML, with at least 3 years in Generative AI and LLMs.
• Strong proficiency in Python and ML libraries such as Scikit-learn, XGBoost, LightGBM, CatBoost.
• Deep understanding of LLMs including OpenAI (GPT-4, GPT-4o), Claude, Gemini, LLaMa, DeepSeek, etc.
• Proficiency with GenAI tooling: Langchain, Langfuse, Crew AI, LLAMA Index, Langgraph, etc.
• Experience working with vector databases (Pinecone, FAISS, OpenSearch, Chroma) and indexing strategies.
• Hands-on with deep learning frameworks such as PyTorch and TensorFlow.
• Strong experience with AWS services: SageMaker, Bedrock, DynamoDB, S3, Lambda, etc.
• Proficiency in REST API development using FastAPI, Uvicorn, Flask, Docker, and related tools.
• Strong database knowledge-both SQL (PostgreSQL) and NoSQL (DynamoDB).
• Familiarity with caching systems like Redis and Memcached.
• Strong communication skills and ability to lead discussions with both technical and non-technical stakeholders.

Preferred:

• Experience in leading enterprise-scale AI/ML deployments.
• Contributions to open-source GenAI/ML projects.
• Certifications in AWS AI/ML or equivalent.