Roles & Responsibilities

- Lead end-to-end design and delivery of production-grade AI/ML solutions including RAG pipelines, LLM-based applications, and extraction systems
- Architect and develop robust, scalable AI/ML services in Python with focus on reliability and production-grade performance
- Develop and optimize AI-driven extraction workflows using document parsing, chunking, embeddings, RAG, and LLM-based extraction methods
- Deploy and scale AI models on AWS and Azure (SageMaker, Bedrock, Azure AI Foundry) with seamless integration into data pipelines
- Build and maintain CI/CD pipelines for AI model deployment using GitHub Actions, Azure DevOps, Docker, and Kubernetes
- Define and implement evaluation frameworks (precision, recall, F1, field-level accuracy) and maintain code quality through reviews and testing
- Partner with Product, Data Engineering, and Platform teams to translate business requirements into scalable AI solutions
- Mentor team members and share knowledge to elevate overall team capability
- Continuously research and apply advancements in NLP, LLMs, and extraction techniques
- Contribute to efficient development cycles following Agile practices and drive automation across the AI delivery pipeline

Ideal Candidate

- Strong Senior AI Engineer Profile with production-grade LLM and Python expertise
- Mandatory (Experience 1): Must have at least 3+ years of professional AI/ML engineering experience with demonstrated track record of delivering production-grade AI systems in real-world environments
- Mandatory (Tech skill 1): Must have solid programming skills in Python and SQL,



with hands-on ML/data libraries (scikit-learn, pandas, numpy) and deep-learning frameworks (PyTorch or TensorFlow), plus REST API design
- Mandatory (Experience 2): Must have hands-on experience building and deploying production-grade ML/LLMs including RAG pipelines, document parsing, information extraction, and text processing on large-scale unstructured data (preprocessing, chunking, embeddings, feature engineering)
- Mandatory (Tech skill 2): Must have strong NLP / extraction-focused ML depth — transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows.
- Mandatory (Tech skill 3): Must have hands-on experience with AWS (SageMaker, Bedrock, EC2, Lambda) and Azure (AI Foundry, Azure OpenAI) for model training, fine-tuning, deployment, and inference at scale
- Mandatory (Tech skill 4): Must have experience with multi-agentic frameworks / orchestration tools (Claude Code, LangGraph, LangChain, CrewAI)
- Mandatory (Tech skill 5): Must have hands-on experience with MLOps ecosystem including experiment tracking (MLflow, Weights & Biases), model versioning/registry, automated retraining, and CI/CD (GitHub Actions, Azure DevOps, Docker, Kubernetes)
- Mandatory (Tech skill 6):



Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).
- Mandatory (Tech skill 6): Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).
- Mandatory (Team Leadership): Must have experience leading projects or teams, managing technical deliverables, and mentoring, with strong problem-solving in ambiguous challenges
- Mandatory (Education) - Bachelor's or Master's degree in Computer Science/Engineering/Data Science/Mathematics/Statistics or related fields
- Mandatory (Company): B2B Tech/Consulting/B2B Software
- Preferred (Certification): AWS certifications (Solutions Architect, Machine Learning Specialty), Azure certifications (AI Fundamentals, AI Engineer Associate), or Databricks certifications (Machine Learning Professional, Generative AI Engineer Associate)
- Preferred (Methodology): Experience in Agile development methodologies
- Preferred (Tools): Data pipeline/orchestration (Apache Kafka, Airflow); certifications — AWS (Solutions Architect, ML Specialty), Azure (AI Engineer Associate), Databricks (ML Professional, GenAI Engineer Associate).

Pay: From ₹100,000.00 per month

Benefits:

- Paid sick time
- Paid time off

Application Question(s):

- Your Current CTC and Your Notice Period

Experience:

- Total: 5 years (Required)

Work Location: In person

📌 Senior AI / ML Engineer (Python / LLM) (Gurugram)
🏢 Qualitrix Technologies
📍 Gurugram