Description:

Role Overview

The Senior Engineer - MLOps and GenAI is a high-impact technical role requiring a minimum of 3+ years of full AI Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale machine learning applications in hosted production environments.

This role is central to the Machine Learning domain, focusing on the technical aspects of deploying and maintaining AI solutions, with mandatory expertise in Generative AI (GenAI), NLP, and MLOps.

The incumbent will drive technical excellence to deliver digital products that support a reliable airline operation.

Job Summary

We are seeking a Senior Engineer (3+ years AI SDLC experience) with mandatory expertise in Python, MLOps tools (MLflow, Kubeflow, Docker, Kubernetes), and the Azure AI Foundry stack (ML Studio, AI Search).

The ideal candidate will implement and optimize Python-based ML pipelines, focusing on model scalability, efficiency, and responsible AI governance.

Key responsibilities include designing, deploying, and monitoring classical ML and GenAI solutions (LLMs, RAG), ensuring post-deployment observability and collaborating closely with data scientists to integrate models into core applications using Domain Driven Design and TDD principles.

MLOps, Deployment, and Pipeline Engineering :

- Implement and optimize Python-based ML pipelines for data preprocessing, model training, versioning, and deployment, ensuring high performance and reliability.

- Work closely with data scientists and product teams to build and deploy AI solutions, focusing on technical aspects of deployment, scalability, and resource management.

- Write and maintain production-grade code for model training and deployment, collaborating with software engineers to integrate models into enterprise applications using Domain Driven Design and Test-Driven Development (TDD).

- Utilize MLOps Tools such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes to manage the full model lifecycle.

- Proficiency in post-deployment model maintenance, including observability, monitoring, and drift detection strategies to ensure sustained model accuracy in production environments.

Generative AI and NLP Expertise:

- Apply a Strong understanding of GEN AI & NLP concepts, including LLMs, tokenization, embeddings, transformers, and attention mechanisms.

- Experience developing and implementing generative-based AI solutions using Large-Language Models (LLMs) (e.g., Open AI GPT, Google Gemini, Llama).

- Leverage Knowledge of Vector Databases (e.g., Pinecone, FAISS, Weaviate) and implement effective retrieval-augmented generation (RAG) strategies.

- Possess Expertise in Prompt Engineering, including designing and optimizing prompts for foundation models to enhance output quality and control.

- Utilize Azure AI Foundry services, including Azure ML Studio, AI search, Semantic Kernels, Semantic Cache, and Content safety filters.

Architecture, Governance, and Development Standards:

- Collaborate with leaders, architects, and technical leads to understand requirements and develop solutions according to business needs for AI solutions.

- Maintain and enhance existing enterprise services using domain driven design and test-driven development principles.

- Experience developing and implementing governance frameworks and controls for responsible AI, including knowledge of various AI regulations, bias mitigation, and explainability.

- Proficiency in object-oriented design techniques and principles for building robust and scalable applications.

- Utilize Build/deployment tools like Maven, Gradel, Git, Junit, and Mockito and the DevOps Toolchain (Nexus, SonarQube, Jenkins, ADO Pipelines) for CI/CD.

Mandatory Skills & Qualifications

- Experience: 3+ years of full AI Software Development Life Cycle (SDLC) experience and 3+ years of professional, design, and open-source experience.

- Core Technology: Proficiency in Python.

- Cloud & Tools: Experience with Microsoft Azure and Databricks. Mandatory proficiency in MLOps Tools such as MLflow, Docker, and Kubernetes.

- AI/GenAI: Strong understanding of GEN AI & NLP concepts (LLMs, RAG, tokenization, embeddings).

- Governance: Experience implementing governance frameworks for responsible AI (bias mitigation, explainability).

Preferred Skills :

- Experience: 5 years of full AI SDLC experience.

- Domain: Airline Industry experience.

- Database: Expertise with persistence frameworks (Hibernate, Oracle, ORM) and query performance tuning.

- Frameworks: Experience with AI/ML Frameworks like TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face.