Senior AI / ML Engineer (Python / LLM)

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 strong 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