Applied Machine Learning Engineer Lead Consultant

Job Description

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.

Job DescriptionThis lead consultant is a hands-on, forward engineering role in the field of machine learning, information retrieval, artificial intelligence, natural language processing, and ontology engineering technologies. Contributes to the realization of cutting-edge technical capabilities into business applications and solutions by being responsible for applying advanced algorithms and techniques to software solutions. About the RoleWe are looking for a Generative AI Software Engineer to join our team and help build next-generation AI-driven solutions. This role blends traditional Software engineering with cutting-edge AI integration, enabling innovative digital products and services.

You will work closely with cross-functional teams to design, develop, and deploy secure, scalable applications and integrate advanced AI models into production environments. Key ResponsibilitiesSofware EngineeringBuild secure, scalable, and high-performance microservices and applications using Java Spring Boot / Python.

Design and maintain RESTful APIs and microservices architecture with asynchronous processing. Implement CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Deploy and manage applications on cloud platforms, preferably Microsoft Azure.

AI Integration & DevelopmentIntegrate and deploy Generative AI models (e. g. , OpenAI, Hugging Face, LangChain) into production environments.

Optimize LLMs for specific use cases and implement RAG (Retrieval-Augmented Generation) pipelines. Work with embedding models, vector databases, and prompt engineering techniques.

Explore multi-modal AI systems and agentic AI frameworks for advanced capabilities. Modern Development PracticesLeverage tools like GitHub Copilot and agentic AI for code reviews, unit testing, and pull requests. Leverage APM tools like DataDog to enhance Observability posture for your application.

Collaborate with platform consultants, product engineers, and digital product managers to integrate AI solutions. MLOps & Model DeploymentImplement best practices for model deployment, scaling, versioning, and monitoring. Develop and maintain scalable data pipelines for ingestion, processing, and feature engineering.

Ensure compliance with ethical AI standards and data governance as per Allstate standards. Required Qualifications3+ years of backend development experience using Java Spring Boot / Python. Strong understanding of RESTful APIs, microservices architecture, and asynchronous processing.

Hands-on experience with Docker, Kubernetes, and CI/CD pipelines. Experience working with Generative AI APIs and/or open-source models. Knowledge of LangChain, LLM orchestration, and prompt engineering.

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