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Allied Solutions

Data-driven insurance and lending risk management

AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeCarmel, IN, USANo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in computer science, artificial intelligence, data science, or a related field is required; relevant work experience may be considered as an equivalent. A master's degree is preferred.
  • At least four years of professional experience in artificial intelligence or related fields is required.
  • Experience developing and implementing AI models and systems.
  • A portfolio of projects or open-source contributions demonstrating expertise in artificial intelligence.
  • Proficiency in Python, R, or Java.
  • In-depth knowledge of machine learning frameworks such as TensorFlow and PyTorch, and libraries such as scikit-learn and NLTK.
  • Ability to work with large datasets and complex algorithms, with proficiency in data structures, statistical modeling, and computer science fundamentals.
  • Ability to explain complex technical concepts to non-technical stakeholders.
  • Ability to work independently and collaboratively, meet deadlines under pressure, and think strategically and tactically.

Responsibilities

  • Configure, connect, and extend AI-enabled solutions using enterprise AI platforms, commercial products, automation tools, integrations, and lightweight supporting components.
  • Design and build secure, reusable connections that enable enterprise AI platforms to access approved data, services, and business actions using APIs, connectors, orchestration tools, and standards such as Model Context Protocol.
  • Build and validate proofs of concept to confirm feasibility, usability, performance, and expected value before broader implementation.
  • Advance assigned solutions through testing, production readiness, launch, and operational handoff within the team's delivery priorities and practices.
  • Troubleshoot implementation issues and collaborate with platform, architecture, security, data, vendor, and business partners to resolve constraints.
  • Work with business stakeholders and the AI Architect to understand assigned workflows, users, pain points, desired outcomes, and measures of success.
  • Translate approved use cases into implementable requirements and acceptance criteria, identifying required data, access, dependencies, and delivery constraints.
  • Validate proposed future-state workflows through demonstrations, prototypes, and user feedback, surfacing practical implementation considerations and appropriate human decision points.
  • Provide estimates, technical findings, risks, and implementation options to support solution and delivery decisions.
  • Maintain understanding of enterprise platforms, approved technologies, data assets, integration capabilities, and reusable services.
  • Evaluate candidate capabilities through hands-on research and experimentation, including generative AI, predictive machine learning, rules-based automation, analytics, and existing platforms.
  • Document feasibility, performance, integration needs, implementation effort, limitations, and support considerations; work with the AI Architect and platform owners to ensure the selected approach follows enterprise patterns and guardrails.
  • Develop solution recommendations based on business fit, implementation speed, security, integration, cost, scalability, and ongoing support needs.
  • Implement applicable responsible AI, privacy, security, legal, accessibility, and data-governance requirements.
  • Define and execute evaluations appropriate to the solution type, including business effectiveness, usability, accuracy, precision and recall where applicable, groundedness, bias, drift, failure handling, human oversight, and escalation.
  • Implement appropriate monitoring, feedback mechanisms, documentation, and support procedures.
  • Consider maintainability, platform alignment, vendor dependencies, technical debt, and operational overhead in implementation decisions.
  • Partner with the Enablement Lead and business teams to provide guidance, demonstrations, training, and other support for effective adoption.
  • Gather usage information, user feedback, business results, and relevant platform or vendor changes to recommend improvements, simplification, scaling, replacement, or retirement.
  • Create and share reusable configurations, workflow patterns, implementation documentation, and lessons learned.

Desired Qualifications

  • Cloud computing experience with services such as AWS, Azure, or Google Cloud.

About the Company

Allied Solutions

Data-driven insurance and lending risk management

Allied Solutions provides insurance, lending, risk management, and data-driven products to financial institutions across North America. It offers turnkey solutions that combine policy administration, compliance, portfolio management, and marketing support, with products such as collateral insurance tracking, lender-placed insurance, credit insurance, debt protection, and asset-protection tools, delivered through technology-based services. The company differentiates itself by operating as an independent Securian Financial subsidiary, focusing on banks and credit unions with a broad, tech-enabled, customized product suite. Its goal is to help financial institutions manage risk, grow lending, and protect consumers by delivering integrated, data-driven insurance and lending solutions through a dedicated service model, including investments in data platforms like PortX.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Carmel, IN
Founded
1978

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