Software Engineer (AI/GenAI Platforms)

Allstate • Dallas, TX

2d

About The Position

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 Description Our Mission We are on a mission to unlock business value from petabyte-scale unstructured enterprise data by building cutting-edge AI, GenAI, and Agentic AI capabilities on top of our Unstructured Data Platform. In this role, you’ll help transform massive volumes of documents, voice recordings, images, and video into actionable intelligence, powerful insights, and autonomous AI systems that drive real business decisions. You will design and build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI to power next‑generation enterprise capabilities. What You’ll Bring Core Engineering Skills Python (required) for AI/ML development Java, with hands-on experience building backend services and enterprise integrations Ability to work across both Python and Java codebases, integrating AI/ML components into Java-based enterprise systems Proven experience building and operating production-grade AI/ML systems Strong understanding of data pipelines and distributed data processing AI / GenAI Expertise Hands-on experience in one or more of the following areas: Large Language Models (LLMs): Working with foundation models and fine-tuning Retrieval Augmented Generation (RAG): Building context-aware AI applications Vector Search & Embeddings: Semantic search and similarity matching Multimodal AI: Processing text, voice, images, and video AI Agents / Agent Frameworks: Building autonomous AI workflows Prompt Engineering: LLM orchestration and optimization Semantic Models: Building and leveraging semantic data models Framework Experience LangChain, LlamaIndex, Semantic Kernel Hugging Face OpenAI, AWS Bedrock, Azure OpenAI Data & Platform Technologies Experience working in large-scale enterprise data environments, including: Architecture Data lakes and lakehouse architectures Analytics Microsoft Fabric, Azure Fabric, or similar analytics platforms Streaming Kafka and event-driven architectures Cloud Services Amazon Web Services (AWS) Datastores MongoDB Atlas Amazon DocumentDB Vector databases (nice to have) ML / AI Platforms Amazon SageMaker or similar ML platforms AWS Bedrock for foundation model access and deployment Model training, evaluation, and deployment Experience with MLOps workflows Observability & Reliability Monitoring and troubleshooting AI and data pipelines Experience with observability tools such as Datadog and AWS CloudWatch Why Join Us? Work on petabyte-scale unstructured data challenges Build with the latest GenAI and Agentic AI technologies Transform unstructured data into enterprise intelligence Join a team shaping the future of AI-powered decision making #LI-JK1 Skills Amazon SageMaker, Amazon Web Services (AWS), Apache Kafka, Communication, Continuous Integration Software, Data Analysis, Large Language Model (LLM) Fine-Tuning, Machine Learning (ML), Python (Programming Language), Semantics, Software Development, Vector Databases Compensation Compensation offered for this role is 85,000.00 - 145,075.00 annually and is based on experience and qualifications. The candidate(s) offered this position will be required to submit to a background investigation. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact. Allstate generally does not sponsor individuals for employment-based visas for this position. Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component. For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance. For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance. To view the “EEO Know Your Rights” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs. To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint. It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment. At Allstate, we work hard to help people live a good life every day. Allstaters are dedicated to serving clients, customers, and communities, which allows employees to find meaning and value in their work. Allstate offers an environment that fosters innovative thinking where you’ll be able to explore your ideas and feel proud of the work you do. Allstate helps protect nearly 16 million households with auto, home, life, and retirement products. We want every professional connected to Allstate to be committed to giving our customers the best and that means finding the best talent. We want you to be our next great addition. It’s easy to search and apply for a new opportunity with Allstate. Simply use the links below to identify the openings that interest you. About Us

Requirements

• Python (required) for AI/ML development
• Java, with hands-on experience building backend services and enterprise integrations
• Ability to work across both Python and Java codebases, integrating AI/ML components into Java-based enterprise systems
• Proven experience building and operating production-grade AI/ML systems
• Strong understanding of data pipelines and distributed data processing
• Hands-on experience in one or more of the following areas: Large Language Models (LLMs): Working with foundation models and fine-tuning Retrieval Augmented Generation (RAG): Building context-aware AI applications Vector Search & Embeddings: Semantic search and similarity matching Multimodal AI: Processing text, voice, images, and video AI Agents / Agent Frameworks: Building autonomous AI workflows Prompt Engineering: LLM orchestration and optimization Semantic Models: Building and leveraging semantic data models
• LangChain, LlamaIndex, Semantic Kernel
• Hugging Face
• OpenAI, AWS Bedrock, Azure OpenAI
• Experience working in large-scale enterprise data environments, including: Architecture Data lakes and lakehouse architectures Analytics Microsoft Fabric, Azure Fabric, or similar analytics platforms Streaming Kafka and event-driven architectures Cloud Services Amazon Web Services (AWS) Datastores MongoDB Atlas Amazon DocumentDB
• Amazon SageMaker or similar ML platforms
• AWS Bedrock for foundation model access and deployment
• Model training, evaluation, and deployment
• Experience with MLOps workflows
• Monitoring and troubleshooting AI and data pipelines
• Experience with observability tools such as Datadog and AWS CloudWatch

Nice To Haves

• Vector databases

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed