AI Engineer

Allied Solutions is seeking an AI Engineer in Carmel, IN to architect, fine-tune, and deploy AI solutions that streamline operations and generate actionable insights. This onsite role focuses on building AI-enabled capabilities, validating feasibility, and supporting responsible implementation through launch and adoption.

Key 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 allow enterprise AI platforms to access approved data, services, and business actions via APIs, connectors, orchestration tools, and emerging standards such as Model Context Protocol (MCP).
• Develop and validate proofs of concept to confirm feasibility, usability, performance, and expected value prior to broader rollout.
• Advance assigned solutions through testing, production readiness, launch, and operational handoff aligned with team delivery priorities and practices.
• Troubleshoot implementation issues and collaborate with platform, architecture, security, data, vendor, and business partners to address constraints.
• Partner with business stakeholders and the AI Architect to understand the assigned workflow, users, pain points, desired outcomes, and measures of success.
• Convert an approved use case into implementable requirements and acceptance criteria, including identification of needed data, access, dependencies, and delivery constraints.
• Validate future-state workflows through demonstrations, prototypes, and user feedback, including considerations for human decision points.
• Provide estimates, technical findings, risks, and implementation options to support solution and delivery decisions.
• Maintain familiarity with Allied’s 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 to inform decisions, ensuring selected approaches follow enterprise patterns and guardrails with the AI Architect and platform owners.
• 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 appropriate evaluations, including business effectiveness, usability, and applicable model metrics (accuracy, precision/recall), as well as groundedness, bias, drift, failure handling, human oversight, and escalation.
• Implement monitoring, feedback mechanisms, documentation, and support procedures.
• Consider maintainability, platform alignment, vendor dependencies, technical debt, and operational overhead when making implementation decisions.
• Work with the Enablement Lead and business teams to deliver guidance, demonstrations, training, and other support needed for adoption.
• Collect usage information, user feedback, business outcomes, 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.

Required Qualifications

• 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 for education requirements.
• 4+ years of professional experience in AI or related fields is required.
• Experience developing and implementing AI models and systems.
• Portfolio of projects or contributions to open-source projects demonstrating AI expertise.
• Proficiency in programming languages: Python, R, or Java.
• In-depth knowledge of machine learning frameworks: TensorFlow and/or PyTorch, and libraries such as scikit-learn and NLTK.
• Strong ability to work with large data sets and complex algorithms.
• Proficiency in data structures, statistical modeling, and computer science fundamentals.
• Excellent problem-solving skills and the ability to think algorithmically.
• Strong communication skills, including the ability to explain 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.
• Strategic and tactical thinking.

Preferred Qualifications

• Master’s degree preferred.
• Experience with cloud computing services (AWS, Azure, Google Cloud) is a plus.

Technology Stack

• 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.