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Allstate · 13 hours ago

AI Software Engineer Associate Manager

United States

Full-time

Remote

Senior Level, Lead/Staff

$100K/yr - $170K/yr

8+ years exp

Allstate is a company dedicated to protecting families and their belongings from life’s uncertainties. They are seeking a highly experienced Associate Managing Engineer to lead the design, development, and delivery of next-generation digital products, with a focus on Large Language Models and Generative AI integration.

BankingFinanceFinancial ServicesInsuranceInsurTechVenture Capital

No H1B

Responsibilities

Lead and manage a global engineering team of engineers, overseeing recruitment, onboarding, regular one-on-one meetings, performance reviews, and career development. Inspire and influence peers, direct reports, and stakeholders to achieve business objectives and embrace change

Facilitate and participate in agile ceremonies, including daily standups, inception and iteration planning, backlog refinement, and retrospectives. Collaborate closely with product managers to ensure technical input informs product scope and delivery

Actively contribute to software development efforts, writing, reviewing, and guiding code to ensure high-quality, scalable, and secure implementations. Balance technical leadership with hands-on coding to drive project success and mentor the team through example

Architect and design secure, scalable digital products with a focus on Large Language Models (LLM), Generative AI, and Retrieval Augmented Generation (RAG) systems. Provide technical leadership and mentorship on best practices in AI, MLOps, Azure AI Services, and software development technologies including Java and SQL

Drive cross-functional collaboration and align engineering strategy across product portfolios, partnering with product managers, stakeholders, and other departments to deliver cost-effective technology solutions. Adapt communication style to engage diverse internal and external audiences

Act as a subject matter expert in Generative AI, LLM fine-tuning, and cloud-native Azure integration, championing innovation and continuous learning across the organization

Qualification

Large Language ModelsGenerative AICloud-native AWS/AzureMicroservices architectureJavaPythonMLOpsKubernetesREST APIsAgile methodologiesStakeholder CommunicationData governanceUI/UX PrinciplesLeadership

Required

4 year Bachelor's Degree

Hands-on experience architecting, designing, implementing, and delivering large-scale distributed systems and cloud-native microservices following 12-factor app principles

8+ years developing microservices at scale, preferably using Java and Spring Boot, with strong expertise in design patterns, object-oriented principles, and code quality best practices

Ability to build Python-based AI agentic services and integrate them into existing enterprise systems

Solid understanding of distributed systems, RESTful APIs, databases, and security best practices

Experience designing, implementing, and managing REST APIs including documentation, versioning, service discovery, testing, and API gateway integration

Knowledge of web and API security frameworks

Backend development expertise including relational databases (MS SQL Server), NoSQL (MongoDB, Document DB), vector databases, caching, Kafka, and container orchestration with Kubernetes

Strong data modeling and database management skills, including Azure Data Lake Storage (ADLS), data governance, and data pipeline design for large-scale ingestion and processing

Strong expertise in AWS / Microsoft Azure Cloud Platform is required

Experience working in Agile environments, including Extreme Programming (XP)

UI development experience (preferably React) with knowledge of component architecture and state management

Proven leadership, stakeholder relationship management, and people management skills

Ability to plan, prioritize, and manage software development lifecycles effectively

Experience with data fabric architectures enabling unified, secure, and governed access to distributed data assets across hybrid and multi-cloud environments

Strong expertise in Microsoft Azure Cloud Platform including Azure AI Services, Azure OpenAI Service, Azure AI Search, and Azure Machine Learning

Hands-on experience integrating AI/ML microservices into enterprise systems

Proficiency with LLM orchestration frameworks such as LangChain or Semantic Kernel

Practical experience implementing RAG architectures using vector databases for high-performance data retrieval

Experience with MLOps practices for LLMs including model versioning, CI/CD pipelines, deployment automation, and production monitoring

Skilled in designing and managing data pipelines for LLM applications involving embedding generation, data chunking, indexing, and integration with cloud data stores

Experience developing and deploying predictive models and AI-driven data pipelines that ingest, transform, and operationalize data to support real-time and batch predictions