AI Solution Engineer

This is a fully remote position, open to applicants in Alabama, +42 more states.

📋 Description

• Design, develop, assess, and launch multi-step AI agents and services powered by LLM into production.

• Create AI agents that access governed data, utilize internal APIs and tools, make bounded decisions, and escalate issues to humans when necessary.

• Engineer definitions for tools/functions, data retrieval and grounding, state and memory management, orchestration, retries, failure handling, as well as cost and latency oversight.

• Develop golden datasets, conduct offline and online evaluations, create regression suites, facilitate human-in-the-loop reviews, and establish guardrails.

• Instrument and manage production systems with tracing, monitoring, drift and quality alerts, along with clear ownership responsibilities.

• Create reusable components for the shared services portfolio.

• Collaborate with vertical leaders to pinpoint and define high-value use cases.

• Convert business challenges into solution designs and set up reference architectures and preferred methodologies.

• Provide guidance on build-versus-buy decisions and assess whether an agent, model, rule, or fixed process is most suitable.

• Construct and validate forecasting, propensity, segmentation, and anomaly-detection models.

• Engineer Lakehouse features and pipelines that serve models and agents.

• Design baselines, holdouts, A/B tests, quasi-experimental measurements, and defensible outcome evaluations.

• Effectively communicate technical outcomes to engineers and distribution executives.

• Document intended use cases, limitations, assumptions regarding training data, testing, and monitoring strategies.

• Maintain the model inventory while implementing de-identification and least-privilege access protocols.

• Identify fairness and unfair-discrimination risks and direct issues for actuarial and compliance review.

• Develop auditable systems with reproducible code, lineage, methodology, and compliant recordkeeping.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, or a related technical discipline, or equivalent experience with a robust portfolio of delivered projects.

• 6–10 years of collective experience in software, data, or AI/ML engineering.

• Minimum of 2 years of hands-on experience with LLM-based systems.

• Must possess authorization to work in the United States without sponsorship.

• Over 3 years of experience in building AI or ML systems in production, including designing and deploying LLM-powered agents or multi-step AI workflows.

• Practical fluency in at least one agent framework or Software Development Kit (SDK).

• Familiarity with tool and function calling, internal APIs, structured outputs, RAG, vector search, prompt and context engineering, systematic AI evaluation, and guardrails.

• Strong hands-on experience with Databricks, including notebooks, clusters, jobs, workflows, and production-level code.

• Advanced proficiency in SQL and solid knowledge of PySpark.

• Experience with Unity Catalog, Delta Lake, medallion architecture, and MLflow.

• Production experience on Microsoft Azure, including Azure OpenAI or Azure AI Foundry.

• Strong Python engineering expertise with Git-based version control.

• Experience in API design and integration, REST, authentication, secrets management, and enterprise systems integration.

• Proficiency in Docker and Continuous Integration/Continuous Deployment (CI/CD) for data and AI workloads.

• Understanding of cloud-native architecture, identity and Role-Based Access Control (RBAC), and data governance in a regulated environment.

• Foundation in statistical modeling and machine learning.

• Experience in building and validating supervised models on structured data, with at least one successfully taken to production.

• Experience in time-series forecasting, hypothesis testing, and rigorous model evaluation.

• Capability to handle missing values, class imbalance, drift, and inconsistent source systems.

• Ability to engage effectively with non-technical business leaders.

• Comprehensive ownership of production from problem definition through deployment, adoption, and iteration.

• Experience leading project delivery at the project or pod level.

• Excellent written and verbal communication skills.

• Background screening required.

🏝️ Benefits

• Paid Time Off (PTO)

• Medical insurance

• Dental insurance

• Vision insurance

• Retirement savings plan

• Disability insurance

• Life insurance

• Occasional travel to AmeriLife business locations and affiliate sites