AI Engineer

Allied Solutions; Carmel (IN); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, dental and vision insurance

100% company-paid life and disability

401k with company match

Three weeks PTO

Career growth opportunities

Job summary

Allied Solutions seeks an AI Engineer to architect, fine-tune, and deploy AI solutions that streamline operations and surface insights. The role focuses on building secure, reusable connections and evaluating feasibility with proofs of concept.

The candidate will collaborate with the AI Architect and stakeholders to translate use cases into actionable requirements, while upholding Responsible AI and governance standards.

Qualifications

• BS degree in CS/AI/Data Science or related field required.
• MS degree preferred; relevant work experience may substitute.
• 4+ years in AI or related fields required.

Responsibilities

• Architect, fine-tune, and deploy AI solutions driving insights.
• Design secure, reusable connections for data access via APIs.
• Build proofs of concept to assess feasibility and value.
• Collaborate with stakeholders and AI Architect on outcomes.
• Translate use cases into implementable requirements and criteria.
• Ensure compliance with Responsible AI, privacy, and governance.
• Document feasibility, risks, and options for decisions.
• Deliver evaluations on effectiveness, bias, and drift.
• Monitor, document, and support deployed solutions.
• Maintain knowledge of Allied's platforms and services.

Skills

AI engineering

Python

Machine learning

Cloud computing

Data analysis

Education

Bachelor's degree in CS/AI/Data Science

Master's degree preferred

Tools

TensorFlow

PyTorch

scikit-learn

NLTK

Job description

Allied Solutions is seeking an AI Engineer to architect, fine-tune, and deploy AI solutions that streamline operations and surface insights.

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 so enterprise AI platforms can access approved data, services, and business actions via APIs, connectors, orchestration tools, and emerging standards such as Model Context Protocol (MCP).
• Build and validate proofs of concept to confirm feasibility, usability, performance, and expected value.
• Advance assigned solutions through testing, production readiness, launch, and operational handoff aligned to delivery priorities and team practices.
• Troubleshoot implementation issues and coordinate with platform, architecture, security, data, vendor, and business partners to address constraints.
• Collaborate with business stakeholders and the AI Architect to understand workflow, users, pain points, desired outcomes, and measures of success.
• Translate an approved use case into implementable requirements and acceptance criteria, including required data, access needs, dependencies, and delivery constraints.
• Validate future-state workflows through demonstrations, prototypes, and user feedback, including surfacing practical implementation considerations and appropriate human decision points.
• Provide estimates, technical findings, risks, and implementation options to support solution and delivery decisions.
• Maintain strong knowledge of Allied's enterprise platforms, approved technologies, data assets, integration capabilities, and reusable services.
• Evaluate candidate capabilities via 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 with the AI Architect and platform owners to ensure enterprise patterns and guardrails are followed.
• 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 monitoring, feedback mechanisms, documentation, and support procedures.
• Account for 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 to drive 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.

Requirements

• Bachelor's degree in computer science, Artificial Intelligence, Data Science, or a related field is required.
• Master's degree preferred.
• Relevant work experience may be considered as an equivalent for education requirements.
• 4+ years of professional experience in AI or related fields required.
• Experience developing and implementing AI models and systems.
• Experience with cloud computing services (AWS, Azure, Google Cloud) is a plus.
• Portfolio of projects or contributions to open-source projects demonstrating AI expertise.
• Proficient in programming languages such as Python, R, or Java.
• In-depth knowledge of machine learning frameworks (TensorFlow, PyTorch) and libraries (scikit-learn, NLTK).
• Strong ability to work with large data sets and complex algorithms.
• Proficient in data structures, statistical modeling, and computer science fundamentals.
• Excellent problem-solving skills and ability to think algorithmically.
• Strong communication skills, including explaining complex technical concepts to non-technical stakeholders.
• Analytical and decision-making skills.
• Ability to work independently and as part of a team.
• Ability to meet deadlines and work under pressure.
• Ability to think strategically and tactically.

Technologies

• Python, R, Java
• TensorFlow, PyTorch
• scikit-learn, NLTK
• AWS, Azure, Google Cloud
• Model Context Protocol (MCP)

Benefits

• Medical, dental and vision insurance coverage
• 100% company-paid life and disability coverage
• 401k options with company match
• Three weeks PTO by the end of the first year
• Career growth opportunities for employees of all levels

Location: Carmel, IN (onsite)

Minimum experience: 4 years